Yes, it's now time for Member Statements, the member from Wellington Hall of Wales. Mr Speaker, yesterday after question period I was very glad to tell the Minister of Health about the very successful walk or run for Georgetown Hospital, which my wife Lisa and I attended this past Sunday morning. This annual walk is a great community event, and this year raised $37,000 for the Georgetown Hospital. Our Georgetown Hospital Foundation staff and volunteers do an amazing job, and I especially want to acknowledge Jennifer McNally, the Foundation's manager for annual giving and special events. The money raised by the Foundation is spent to improve health care services through the purchase of medical equipment and enhancements to the hospital's programs and facilities. I try to attend the walk every year, and I was glad to see Halton Hills Regional Counselor, Jane Fogel, and Town Counselor John Hearst there as well. Since the Georgetown Hospital opened its doors in 1961, it's been a pillar in our community providing outstanding health care services to local residents. In 2011, I was glad to help secure a promise from the government of up to $2.6 million to support needed renovations at the hospital. In addition to the province's commitment, money raised in the community paid for most of the project. After working together, we now have a new emergency room, CT scanner, and upgrades to the diagnostic imaging department, better health care closer to home. Someday, we'll need a brand new Georgetown Hospital. It goes without saying that I would want to support whatever hospital redevelopment project our community submits to the ministry. I want to thank everyone involved. Working together, we make progress. Thank you very much, Mr. Speaker. Thank you. Further member statements? The member from Windsor West. Thank you, Speaker. It's my pleasure to stand in the house today to talk about a young lady. Now, I know it's not usually polite to talk about women's ages, but I'm going to guess that Maya is probably about 11 years old, and she's quite an exceptional young lady. Maya McHale is the founder of Maya's Friends, a group of 22 young girls, and occasionally they have a young fellow or two that come out and help who have raised funds to help those in need in my riding of Windsor West as well as across all of Windsor and Essex County. As a result of their yearly signature fundraising event, Maya's lemonade stand. Maya and her friends raised $3,288 as well as collecting hundreds of cans of food. They have donated the food and the canned goods and the money that they collected to the downtown mission, the Salvation Army, and the Windsor Youth Center, which we lovingly refer to as the WIC. They all benefit from the fundraising efforts and the generosity of Maya's friends. Also notable is the partnership between Maya's team and the Real Canadian Superstore. They are generously donate gift cards and food items at cost in order to maximize the efforts of Maya's friends and their number of low income or homeless residents of Windsor and Essex County. It is with great pride that I stand in the legislature and thank Maya and her team of friends for their continued efforts to make life a little bit easier for those living in poverty. Thank you. Member Sting, it's the member from Tumblin, 20 West. Well thank you, Speaker. Mr. Speaker, it gives me great pleasure to be able to take this opportunity to thank my colleagues from all sides of the house for taking time out their busy schedule in supporting Tumblin, 20 West Day last Thursday. I was proud to showcase my riding to remind them of the exciting things going on in Eastern Ontario. Mr. Speaker, I tell you the day was a great success and I'm truly grateful for the support shown by all members and their staff who attended. I'd also like to thank the many businesses and organization who participated in showcasing only a small portion of the amazing things that Northumblin, 20 West has to offer. People like Betty Potter-Tarts, Burnham Family Markets, Northumblin County Economic Development Tourism, William Street Brewery, Quinty West Economic Development, City of Quinty West, Rachel Tarts, Wild Card Brewing Company, Kaley's Kale Chips, Habitat for your mind and Thumblin, Hote Goat, Empire Cheese, The Big Apple, Grills Origin, Mrs. B. Chocolates, Le Boucherre de France, Le Couture Salumi, Nestle Brighton Springs Quicker, Bakery's Tretin and Saputo Cheese Products. This is the third year we have hosted this event and I was very pleased with the participation from our community, which included folks from across the writing as well, the many different products displayed. I'm excited to make next year even a bigger and better event. Thank you, Speaker. Thank you, Speaker. I'd like to take a moment to recognize September as Big Brother Big Sister Month. For over a century, Big Brothers and Big Sisters have been helping Canadian children and youth reach their full potential by providing them with proper mentorship. Currently, Big Brothers and Big Sisters has more than 115 agencies in 1,000 communities across Canada that help more than 42,000 children. In Ontario, Big Brothers Big Sisters helps more than 21,000 children and youth across 500 communities. Mentoring has remarkably changed over the course of time from simply matching a role model in your life, whether it's a teacher, a friend or a family member. Now there are mentoring programs for groups that are designed for different needs, such as the importance of physical activity or eating healthy. Mentoring has profound benefits for a child, including helping a child stay in school, establish a confidence in their ability to do well in school, helping instill in children that school can be enjoyable and teaching the importance of doing well. Even with all of this great work, there are more than 8,000 children and youth in Ontario waiting for that mentoring opportunity. Every child deserves a role model in their life to instill confidence and reach their fullest potential. If you've ever had a role model in your life, you know the profound effect it can have. If you can, I encourage you to donate your time to become a big for Big Brothers Big Sisters and make a difference. Thank you. Thank you. Further member states, the member from Nickelbelt. Thank you, Speaker. Did you know that the OLG has locked out its workers over pension, Speaker? Since September 2019, September 19, Unifier workers working at Sudbury, Woodbine and Brantford were locked out by the OLG. They were locked out by the government. Why? Because those workers want to keep their pension. It's as simple as that. The government has promised that as slots were going to be privatized and give to privatized casino operator that they would have a pension, but they are not willing to say that they will have an opportunity to negotiate their pensions. So what does that mean? That means that Unifier employees that presently have and belong to the public service pension plan won't be allowed to continue into this pension plan. They will have to take whatever the private casino operator has to offer them. This is a shame, and it's pretty hard to believe that this is happening when we have a liberal government that goes out of its way to say that every worker in this province should have a pension plan. Not only do they say this, you cannot flip on any TV channel that you see those ads about the new Ontario retirement pension plan, but then you have a thousand workers that have a pension plan. All they want to do is to keep them when they get privatized, and what do they get? They get to walk the picket lines for the last two weeks. That's a shame. The government has to mandate them back to the negotiation table so they keep their pension plan. Thank you, Mr. Speaker. Polycystic kidney disease, or PKD, is one of the most common life-threatening genetic diseases in the world. It currently affects 66,000 Canadians and over 12.5 million people worldwide, including people in my riding of the Tobacco Centre. There is no cure, Speaker. Last year I had the opportunity to talk to a doctor about the devastating effects of PKD, and what he said was to fight PKD. It's important that we raise awareness, that we raise money to find a cure, but that we also find ways to provide support to those who are suffering with PKD. One organization that has done so much work in helping to combat the disease is the PKD Foundation of Canada. The organization started out in a living room of an Oakville home in 1993 and now has chapters around the country. It raises awareness and funds for research and is awarded hundreds of thousands of dollars in research grants. I was happy to join the PKD Foundation this past Sunday at Centennial Park in my riding of the Tobacco Centre for their annual walk for PKD. Since 2007 the event has raised almost $700,000, including $134,000 last year. The turnout for this year's walk was excellent, and I'm sure there was a great success. While at the event I had a chance to meet with the organization's hard-working team, including Executive Director Jeff Robertson and the rest of the organization's board, I'd like to congratulate them once again on the walk and for all the work that they do to help fight PKD and help those who are fighting PKD. It's with help of organizations like the PKD Foundation that we will do exactly what is needed, continue to raise awareness, raise funds to find a cure, and to support those who are suffering from PKD. Thanks to organizations like the PKD Foundation, we will defeat this disease one day once and for all. Thank you. Thank you very much Mr. Speaker. I'm pleased to share today with my fellow members that this year the Advancing Women Conference will be taking place in Toronto October 5th and 6th. This unique opportunity will focus on recognizing and advancing the role of women in agriculture. The Toronto Conference follows a similar event in western Canada, at which there were roughly 600 women in various agriculture food roles in attendance this year alone. The conference will feature keynote presentations from agricultural leaders, most of whom are women, on topics related to leadership development, finances, career development, community, communication and health. Most importantly, the conference will provide the tools needed to break down Ontario's agri-food glass ceiling by discussing the issues that specifically affect women in this province and across eastern Canada. This event next week in Toronto will also aim to include diverse perspectives from across the industry, from farm owners and operators to the agribusiness sector. This event will bring women together to discuss themes relevant to the agri-food sector as a whole. For instance, the Deputy Minister for the Minister of Agriculture Food and Rural Affairs, Deb Stark, will be speaking about MUD, Mascara and other grand challenges. The Executive Director for the National Organization known as Farm Food Care, Crystal McKay, will be speaking about searching for unicorns, the Loch Ness Monster and work-life balance. Speaker, this will be a great event and with the Commonwealth Women Parliamentarians Ontario outreach program coming to this province on November 5th to 8th, as well as growing my agri-food jobs motion set to occur next week, I look forward to continuing promoting women in the agri-food sector. Thank you. Thank you, Mr. Speaker. I appreciate this opportunity to tell the House about an important milestone in my writing of New Market Aurora. Speaker, 25 years ago, a group of citizens from across Ontario concerned about the ecologically sensitive geography known as the Oak Ridge's Moraine came together to form an advocacy group called STORM, Save the Oak Ridge Moraine. Since 1989, STORM has worked tirelessly at the local and regional levels to ensure municipalities make planning decisions that respect the significance of the Moraine. This past Sunday, supporters gathered in Aurora to celebrate the 25th anniversary of STORM's founding, to celebrate the important contributions the group and its partner organizations have made, and to recognize 25 individuals for the work they've done on behalf of STORM and the Moraine. Speaker, in case anyone needs a refresher, the Oak Ridge's Moraine is a major landform unique to southern Ontario and extends 160 kilometres from the Niagara Scarpen in the west to the Trent River system in the east. Thirteen thousand years ago, as the glaciers began to retreat from southern Ontario, torrential flood channels developed beneath the melting ice-carrying sediments and dumping them into what became the Moraine. Speaker, one of the Moraine's most important functions is the water recharge and discharge area sustaining the health of many watersheds. It's accurately described as southern Ontario's rain barrel. I'm proud to say a good portion of my writing of New Market Aurora sits atop the Moraine and we're richer for it. Congratulations and thank you to STORM for the work it's done in preserving the Oak Ridge's Moraine. Thank you very much. From the member's statements, the member from Eglinton-Lords. Thank you, Mr. Speaker. Yesterday, September 28th, Michael Burgess, a remarkable Canadian, passed away in a Toronto hospice surrounded by friends and family. The 70-year-old Canadian, singer extraordinaire, had been battling cancer for years. Burgess is most fondly remembered for his role in Les Miserables, in which he played Jean Valjean in a more than 1,000 performances. I'm sure a lot of people here were there at the Toronto Royal Alexandria Theatre and toured across Canada. Burgess took the role across Canada on the first national tour of the production and also peered for the 10th anniversary concert to Royal Albert Hall in London. His other major performances include Mano La Mancha, Blood Brothers, and starring roles throughout Canada, the United States. I know I saw him in that incredible feature here in Toronto also. We all can never forget, for instance, when he sang O Canada and our national anthem at Leaf Games for many years. Burgess was also the first person to sing O Canada the World Series in 1992. Michael was born in Regina and spent his formative years in Toronto and went to St. Mike's Choir School just down the street here and later attended the University of Ottawa. Burgess married his fellow Les Miserables performer Susan Gilmore in 1994. We all sadly will miss this incredible voice and I know the Royal Alexander Theatre will dim their marquee lights this evening and we've lost an incredible Canadian whose heavenly voice we will surely miss but now he's singing up there with St. Peter. Rest in peace Michael Burgess.


So, welcome to the 28th lecture of cryogenic engineering under the NPTEL program. In the last lecture we were talking about sterling cycle cryocoolers. So, we have studied the sterling cycle in that and we proved that the COP of sterling cycle is equal to that of COP of Carnot cycle. The COP is highest and it is as high as the COP given by a Carnot cycle working in the same temperature limits. We also found that alpha beta gamma are the different arrangements of sterling cryocoolers and each of them has its own advantages and disadvantages. This classification of alpha beta and gamma of different cryocoolers was based upon the position of or the arrangement of the drive of the piston and a displacer or a piston and a piston arrangements that is used for a sterling cryocooler. We also found that the actual working cycle has a continuous motion of piston or displacer. While in ideal sterling cycle it focuses most on the discontinuous motion of piston and displacer. While in actual case it is not easy to give the discontinuous motion and therefore, we will have a continuous motion of piston and displacer. We will have a non isothermal process while the actual cycle demands the ideal cycle demands isothermal processes. We got in actual system we will have pressure losses and pressure drops alright. So, in fact what we say from here is the actual system will have more of losses. The actual system will try to go to a more practical system and therefore, the ideal system of isothermal processes constant volume processes may not be achieved in actual practice. We studied Schmitt's analysis which was given in 1861 and what we also observed what it serves as a first gaze of dimensions. That means, if I want to design a cryocooler the first gaze would be given by the Schmitt's analysis which can talk about what is the diameter of the piston, what is the stroke of the piston or stroke of the displacer diameter of the displacer depending on whatever arrangement we choose to have. The cooling effect and the work input are denoted by QE and WT respectively and we had derived the expressions for QE and WT for ideal Schmitt's cycle. The only realistic assumption was in the Schmitt's analysis was that it have a continuous motion of piston and displacer while in ideal Schmitt's cycle as I earlier said the continuous motion of displacer and piston is not considered. What is considered is a discontinuous motion of piston and displacer. So, Schmitt's analysis was a step towards a realistic analysis taken in 1861. We also studied that the net cooling effect and the total work input required will be considering losses. While Schmitt's analysis will not consider those losses QE and WT are actually kind of ideal assumption still as far as Schmitt's analysis is concerned. So, if we consider the losses the Q net that is the actual Q delivered actual cooling power delivered will be QE predicted by Schmitt's analysis minus various losses in a system. So, minus sigma losses similarly the work input W total is equal to WT predicted by the Schmitt's analysis plus various losses that is plus sigma losses. So, in order to relate my QE given by Schmitt's losses to the actual case actual Q net delivered I have to calculate all these losses and then subtract those losses from QE that will give me the Q net delivered by a curricular similarly I will have to add all those losses which will cause me more work input to be done and these losses will be calculated and added to the WT calculated by Schmitt's analysis and this will give me WT total for a practical system. Outline of this lecture again extending from cryocoolers now I will go to discuss what are design parameters considering Schmitt's analysis understand the effect of those design parameters and therefore we will have parametric studies again based on Schmitt's analysis then we will have Walker's optimization chart and this is a very important optimum design specifications that could be obtained using Schmitt's analysis and from Schmitt's analysis we will have Walker's optimization chart and here for the first time we will derive those dimensions which will give an optimum combination of all these parameters and finally using this Schmitt's analysis and Walker's design charts will have a design methodology of sterling cryocooler and this would give us a first gaze of dimensions for any cryocooler to be designed for a given cooling capacity alright. So, we will solve all these things and we will have a tutorial at the end so that the usage is known to you ok. Let us have parametric studies in general QE is dependent on both design and operating parameters. So, all the parameters which affect the design of a cryocoolers can be clubbed under two parameters which is design parameters and operating parameters. What are design parameters? The design parameters are the one which cannot be changed. So, once the design is made you cannot change those parameters and therefore, they are mostly related to the design aspect or dimensional aspects. So, if I talk about design parameters and if I talk about those non-dimensionalized design parameters we have got k which is equal to v c by v e the ratio of two volumes two swept volumes then tau is a T c by T e this is basically what cold temperature we have designed this cryocooler for. Once I have designed for a particular cold temperature I cannot change that parameter because the design will be carried out for that T c in mind. Similarly, what is my dead volume ratio which is x?  These all could be clubbed as design parameter. Similarly, we got operating parameters which can be changed later. So, once the design is carried out I can still change the speed if I want to or I can still change the maximum pressure generated in a system by changing the charging pressure of the gas in the system. So, that it affects both p max and p minimum by a formula which we have derived earlier in Smith's analysis. So, these two parameters may be called as operating parameters because they can be changed by operator. They are not an inherent part taken in the design in the sense they can be changed from outside. However, these two parameters have to be considered in design analysis. So, the design is carried out for a particular n or a particular p max, but these parameters can still be changed even after the design is made. These parameters are varied to study the effect on QE. Now, let us see what is the effect of all these parameters on QE which is the cooling load that could be produced by the cryocooler. For an optimum design a compromise between operating and design parameters may be sought. So, all these parameters may give a different variations of different parameters. So, what we have to go is an optimum combination of all these parameters. So, that I get maximum cooling effect or I get minimum power input or I get maximum COP or whatever design optimum design you want to carry it for that that can be optimized as a combination of all these parameters. There are 1, 2, 3, 4, 5, 6, 6 or 7 parameters which needs to be optimized of which we can take few for granted that means they can be fixed and a design can be varied out for remaining 3 or 4 parameters. So, based on the Smith's analysis the variation of heat lifted per unit cycle which is QE upon P max into VT this the QE here is heat lifted per unit cycle P max is maximum pressure and VT is the total swept volume in the system. So, if you see QE upon P max by VT is basically P max into VT is basically a non-dimensional parameter and work input required per unit cycle which is WT divided by P max into VT for the above said non-dimensional number is presented. What does it mean? I will I would like to see what is QE upon P max into VT? Similarly, what is WT upon P max into VT and we can see the variation of all the design and operating parameter as a function so that what is this non-dimensional parameter would be? How does it behave?  So, this parameter basically talks about the cooling effect generated per cycle while this parameter talks about work input required per cycle. It is important to note that QE and WT are non-dimensionalized with a product of P max into P max and volume P max into VT. In the following study let us call QE upon P max into VT as Q max. It is just a simplicity to address these parameters as so we have a Q max which is nothing but QE upon P max into VT and we have W max which is nothing but WT upon P max into VT. So, I would like to study now what are the variation of Q max and W max as a function of different design parameters. So, let us study the effect of Q max and W max and vary those parameters and understand how Q max and W max vary because these are the most important parameters related to the design of a cryocooler. What is the cooling effect I get from this cryocooler? What is the power input to this cryocooler? In fact, this divided by this will become the COP of the system if you understand right because P max into VT is common to both the cases. So, here the most important parameter I would like to see as a function of different parameters. So, let us take the first parameter as a temperature at the expansion space that is the coldest temperature Te for which the entire cryocooler has been designed. This is the Te at which Qe is obtained. So, cooling effect is obtained at a particular temperature Te. So, let us study the effect of this parameter and this is my y axis and this is my x axis and on x axis you can see I have put Te given in Kelvin over here while on the y axis I can show both the parameters as Q max and W max. So, the red curve will show relationship between Q max to Te and the green curve will show the relationship of the W max to Te and these curves are plotted for given parameters as k is equal to 2, x is equal to 1 and alpha is equal to 105 degree. So, these three parameters are kept constant and only Te is varied in order to study the effect of variation of Te on Q max and W max. So, this is what variation you can see. So, consider a chart to study the variation of Q max and W max with variation of Te. Now, what do you see as you go on increase the value of Te that means as the cold end temperature increases it is basically coming to room temperature 300 Kelvin is nothing but room temperature and you can very well understand that as the colder end temperature increases the cooling effect increases that means the Q max value given by this red curve will increase. This is absolutely clear that as you increase the lower end temperature the value of Te the cooling effect will increase while at the same time the power input required will go on decreasing. So, if my cooler end temperature or the expansionist temperature increases the cooling effect increases and the W max or the power input will decrease thereby increasing the COP of the machine. I think this effect is very very clear with the knowledge of refrigeration for example, you have that as the cold end temperature increases refrigeration effect will increase at the same time power input will decrease. So, with the increase in the value of Te let us summarize here Q max increases which is seen by this red curve and W max decreases which is seen by this green curve as a result of which the COP of the system increases and this is what is obvious from this system. The next effect is effect of K which is the ratio of the swept volumes that is Vc by Ve again this curve is plotted for both the parameters Q max and W max and here now we have kept temperatures tau is equal to 3 that means my both the temperature are fixed Tc and Te are fixed the data volume ratio is taken as 1 while alpha is still taken as 105 degrees which is nothing but the phase angle between the expansion and compression volume variations on x axis what has been plotted is K value the plot of Q max and W max versus K for tau x alpha as 3 1 and 105 degrees respectively is as shown in this figure. So, what do you see from this figure? It means that as the swept volume ratio is increased that means as Vc by Ve gets increased the cooling effect Q max will start increasing because the flow rate will increase as my Vc by Ve increases I am getting more and more volume of gas getting compressed over here and similarly because I am compressing more and more gas my power input of the system also will increase thereby increase W max. So, both as the value of K increases the Q max will increase and W max also will increase but can I go on increasing this forever no I cannot at a particular point I will the curve will get flattened over there at a particular point the curve will get flattened over there. So, with the increase in the value of K both Q max and W max increase the COP of the system remains constant because by Smith's analysis the COP of the ideal sterling cycle depends only on the value of tau while we have kept the value of tau to be constant. So, even if I go on increase the value of K W max to Q max ratio will always remain constant at whatever K value we are talking about alright. So, for a given value of X if I go on increase in the value of K it is very important for a given value of tau and X if I go on increase in the value of K and Q max and W max will go on increasing and the curve will get flattened over there because the X value also is limited in that sense the ratio is limited to 1 in this particular case. The COP of the system remains constant because we have seen that the COP of the system depends only on the value of tau while increase of K will not affect the COP but it will increase the Q max as well as WT or W max. The next parameter to be studied is the effect of X or the dead volume ratio. So, again as you say the dead volume in a system is that volume which is not swept by compressor and expander displacer or expander piston that means the whatever volume is there which is not traverse by pistons or displacer is what we call as dead volume. For example, all the heat exchanger volume will be dead volume because it is not travelled by the compressor piston or the expander displacer. So, here when I want to study about effect of X on Q max and W max I have kept now tau K and alpha as fixed K has been taken equal to 1 that means Vc by Ve is equal to 1. So, what do you see from this curves? What you see from this curve is as we increase the value of X that means as we go on increasing the value of dead volume in a system for a given expansion volume because X is nothing but Vd upon Ve. So, if I go on increasing the value of X you can see that the Q max decreases at the same time W max also decreases. So, with the increase in the dead volume ratio both Q max and W max decrease that means additional of dead volume, additional of dead volume is actually detrimental from the performance point of view or from the cooling effect point of view at the same time the work input has also reduced. So, again the COP of the system what you can see from here is going to be remaining constant because COP depends only on the value of tau and this is as far as ideal sterling cycle is concerned in actual system the things will change. What is happening basically? Why in the with the increase of X my Q max decrease as well as my W max decreases. So, increasing the dead volume leads to decrease in the pressure ratio of the system. So, as I got more and more volume now which is not a swept volume which is a dead volume my pressure ratio ratio P max to P minimum will decrease and the moment your P max to P minimum will decrease the ratio decreases it will result in lowering of Q max or cooling effect and therefore, increase in X will result in decreasing the value of Q max. Also will be decrease in pressure drop in a system, but this is not considered pressure drop losses are not considered in a smith's analysis, but in actual system pressure drop losses in system will decrease in this with the result of increase in the value of dead volume ratio. So, what is most important is the pressure ratio in the system decreases and this is what leads to decrease in cooling effect as well as decreasing W max or the power input to the system. Increase the value of X your P max will come down alright and as a result of which the W max will decrease as well as Q max will decrease. However, what does it mean that I should keep value of X to be very small as small as possible this is what one would expect, but that is not a practical solution because in practice some amount of dead volume is always necessary to accommodate the after cooler and the regenerator these are heat exchangers and heat exchanger volumes are nothing, but dead volumes, but there has to be some optimum value of X which should accommodate the dead volume generated because of the presence of after cooler and the regenerator and this is most important this is very very important. So, some amount of dead volume is always important is very very important which will sacrifice some amount of Q max basically while W max will get get lowered. So, we have to have some amount of X which possibly equal to X is equal to 8 I cannot have X is equal to 0 for actual design alright. So, I have to have some value of X or 1.2 or 0.8 or something like that. So, that my regenerator volume and after cooler volume is taken care of. So, effect of X basically one would like to keep X as small as possible, but some amount of X or some amount of dead volume is going to be always existent in a cryocooler. The optimum value of X will determine then the COP of a system alright in actual case in actual system the actual value of COP will be determined by the value of X. There exists a phase angle now we say effect of phase angle on Q max and W max. This phase angle is nothing, but the angle by which the expansion space volume variation lead the compression space volume variation which is what we had seen earlier. So, X axis is plotted with alpha in degrees while these values are taken as tau is equal to 3 K is equal to 2 and X is equal to 1. So, there exists a phase difference between the expander displacer and the compressor piston this could be expander piston also if it is a working as a piston and not as a displacer. This phase angle is vital to produce cold in the system also there exist an optimum phase angle for a system. For example, if the phase angle is 0 you will not get any cooling effect this is very important there has to be some phase angle and this phase angle has to be an optimum phase angle basically. So, if I just plot Q max and W max variation against alpha what we can see that both of both this curve go through maximum in the travel during this alpha the variation plots of Q max and W max with alpha are shown over in this figure and what we see both the curve pass through a maximum with an increase in the phase angle. The position of maximum for both the curves occur approximately at the same phase angle what you can see that this is going to be maximum somewhere around 90 very close to 90 and W max is maximum for that phase angle and Q max is maximum for that particular phase angle and also what you can see that also the curve gets flattened near the maximum in the neighborhood of 60 to 120 degree that means this increase is very high and you can see that if I have alpha is equal to 62 kind of 120 the change in this maximum and this value is not that drastic that means I can have an alpha ranging from 60 to 120 if I have to sacrifice this alpha for some mechanical limitation if I cannot have alpha is equal to 90 to touch this peak I can as well have alpha between the 60 to 120 where I say that I do not sacrifice so much on Q max and W max. So, that is why I say that the sensitivity of W max and Q max is not that high in this region while if you go beyond that it is very high in this case in this part below 60 and after 120 the variations in Q max and W max is quite drastic for the variations in alpha and therefore my alpha should I should see that alpha remains between 60 and 120 as far as possible. Now, you have seen that there are so many charts which exist so many parameters which exist and the variation of Q max and W max is different for these variations of the parameters. From the parametric study it is clear that each of the non dimensional parameter has an impact on the performance of the system. However, a combined effect of these parameters on the performance of system as a whole was first reported by Graham Walker in the year 1962 in the form of design charts. So, Walker was the person who first studied all the effect of these parameters and he came up with some design charts and these charts were produced for both refrigerators as well as for sterling engines and they are called as Walker's design optimization chart or Walker's optimization chart. So, he was the one who extended Smith's analysis and got all these parameters optimized and converted those optimization into some kind of design optimization chart and they are called as Walker's optimization chart. So, if I got so much of variations of K X alpha etcetera I can refer to Walker's optimization chart and get those parameters for a cryocooler to be designed for a particular cooling effect at a given T e or a given cooling temperature. So, let us see what are these optimization chart refer to. So, these are the optimization chart Walker has given. So, what you can see for from here is the adjacent figure shows Walker's optimization chart for a refrigerator. Moving from top to bottom this chart has three different axis named Q max. So, you can see that there are three charts 1, 2 and 3 and what you see on the left axis is we have got a Q max which is nothing but Q e upon P max into V t we got alpha the alpha has been given in the radiance as you see here there are three different axis namely Q max alpha in the radiance and K which is volume variation ratio V c by V e and these all things have been plotted across a common T e temperature that means cooling expansion space temperature T e. So, if I know that I have to design a cryocooler at a particular T e say let us say let us say nitrogen temperature which is T equal to 77 Kelvin or oxygen temperature which is 90 Kelvin or whatever temperature you have got in mind I should have that T e over here and if I draw a vertical from here I can get variations of Q max alpha and K as against for different x parameter that is dead volume ratio. So, what parameters do you see here x, K and alpha and also for which a value of Q max is obtained against the temperature of my interest. So, walker charts basically gives parameters K, x and alpha for different cold end temperatures and against that what you obtain is basically the value of Q max and this is what walker chart gives us the value of T c for this all this chart is assumed to be at 300 Kelvin that means T c is 300 and if I want to have tau it is 300 divided by the value of T e which I consider. So, for each of the above set parameter this chart shows the variation of three different values of dead volume ratio which is x is equal to 0.5, 1 and 2 what you see x equal to 0.5 which is this green line x is equal to 1 this is red line and x equal to 2 which is basically the blue line and these three variations are shown over here. If I got any variation between this x 0.7 for example, one can interpolate between these two lines or if I got a 1.2 or 1.5 I can interpolate between this two line linearly and get the variation of Q max alpha or K. From this figure what you see is Q max and K are more sensitive to T e as compared to phase angle alpha it is clear that the alpha variation are these giraffes are quite flattened this cause are quite flattened over there. So, whatever the variation T e happens there is not a drastic change of value of alpha basically is not it while Q max changes drastically as well as the K value changes drastically and that is what one can see from this figure that alpha variation which is given in the radiance is not very very sensitive to T e while Q max and K is quite sensitive. So, with this background of Smith's analysis and Walker's optimization design chart now let us go to the design of a cryocooler. Let us see how we use this analysis and this charts for carrying out a first simple first guess design of a cryocooler to attain a particular temperature T e and to get a cooling capacity of Q e at that particular temperature. The Smith's analysis is a pure ideal analysis and does not take losses into account. We have seen that the only parameter Smith's considers is basically the continuous motion of piston and displacer as against the discontinuation motion demanded by ideal sterling cycle. So, it was the first realistic deviation from ideal sterling cycle which was taken into account by Smith's. However, he had not taken any losses into account. As mentioned in the earlier lecture these losses can be thermal losses, mechanical losses, shuttle conduction, we have got a heat exchanger effectiveness, regenerative effectiveness, we have got a pressure drop across the system and all these losses have to be first calculated properly and they have to be encountered, they have to be understood and net cooling effect for which the cryocooler has to be designed has to be taken into account. That means I require some Q e while I will design Q e for an higher value taking into consideration all these losses that are going to add up to my cooling effect. As a result of which in order to make the analysis more realistic Q e in the walker charts if I want to design my cryocooler based on walker charts whatever Q e has been considered there I will replace that by a parameter called as Q e design. I will not take that as a required Q e, but I will replace that Q e as Q e design for which the cryocooler is designed which is normally I will say 3 to 4 times Q e. In this case I say 3 times Q e that means I will understand that of this 3 times Q e only 1 Q e is designed I mean 1 Q e is desired while one third of this Q e is lost as losses. The required cooling power in order to account for these losses that means I will design this cryocooler for 3 times the value of Q e. What is required by me is only Q e, but I will go for 3 times Q e and which I will refer to as Q e design. I will use this Q e design value for referring to walker charts. So, can I say therefore that Q e design is going to be my 3 times Q e required. If I want to design a cryocooler for 100 watts I will now design it for 300 watts assuming that out of this 300 watts 200 watts are losses and only 100 watts are going to be delivered to the cryocooler to the user basically. Therefore, I will have Q e design taken up as earlier what I have taken as Q e when I refer to walker charts. This is an important consideration design Q e value. So, the design methodology if I want to understand what I will do I will know the value of Q e that is cooling effect required and at what temperature T e. The key steps therefore will be an initial value of x may be assumed. So, what I do first is basically draw a vertical from T e is equal to 77 Kelvin and up to this parameter and assume that x is equal to 1 for example to begin with x may be equal to 1.1, 1.2 or 2 or 0.7 or 0.8. I can determine that later, but in the beginning if I assume that x is equal to 1 from here I will understand what is my Q max value alright. So, I can get a Q max value from over from this may be 0.07 or something from this chart and I will have some assumption I will have some knowledge from mechanical point of view what is my maximum pressure allowed is alright. So, once I know maximum pressure I will know this maximum pressure I will know this Q max I can therefore know what is my total volume that is V t. So, I can know V t now at the same time from other curves I will know what my k is what my alpha is. Once I know this thing what I know now I know my V t value I know the alpha value I know the k value and therefore, with this knowledge I can compute my swept volumes that is V c and V e. I can get my V c and V e therefore, V t from this and I can therefore, come to the first guess of my swept volume V c and V e which will give me what is the diameter of the piston what is the stroke of the piston I can decide what is the ratio of the stroke and stroke the piston diameter could be accordingly now once I get the first guess of all these things I can go back I can see what is corresponding to V c V e my dead volume is is that are these dimensions if not I will again go back and go for x is equal to 1.2 or something like that and do this iteration alright. So, with valid assumptions wherever necessary I will understand what are my dimensions I am going to get are they okay if they are not I can change the value of x now and go back to the top end again and iterate using this optimization chart the very simple first order guess I will get in order to get the value of a particular Q e at a particular T e. Now, as I said earlier I will take this value of Q e in this particular argument over here as 3 times Q e required. So, my I will take design Q e now forgetting the first guess dimension of a cryocooler I will not take a required Q e but I will take 3 times required I can take 4 times required Q e depending on how conservative you want your analysis or you want your design to be I think this design procedure can be well understood by taking a tutorial and therefore, I will you can get a actual number fill and therefore, I will go for a simple tutorial and this tutorial is aiming to design an alpha type sterling nitrogen liquefier this is a nitrogen liquefier using the smith's analysis and using the Walker's chart. Therefore, the working gas is helium and the capacity of the plant is 10 liter per hour of liquid nitrogen. So, I am using helium as the working fluid and the cooling effect should be such that it will cater to 10 liters per hour liquefaction of nitrogen. The maximum allowable pressure that is P max is given to be as 40 bar and the speed of the primer will be 1440 rpm these are mostly standard values. Therefore, I have got a limitation on a maximum pressure that could be generated over here. Now, first and foremost most important thing is calculate my Q e required how much cooling effect will I required in order to get 10 liters per hour of liquefaction of nitrogen gas. So, what I go to I go back to my basics and understand from temperature entropy diagram what is my enthalpy requirement what is my cooling effect requirement in order to get 10 liters per hour of liquid nitrogen. So, this is my alpha type cryocooler which has got a compressor piston and expansion piston also connected through a regenerator. The schematic of an alpha type sterling cryocooler is as shown the given parameters in the problem are evaporation temperature equal to T e which is going to be produced in expansion space over here at 77.2 Kelvin. The compressor temperature is T c which is 300 Kelvin the maximum pressure in the system is going to be P max which is 40 bar n is equal to 1440 rpm these are basically my operating parameters. The parameters to be calculated are what are these volumes V c V e and V c plus V e nothing, but V t. So, what is my total volume in a system especially I am going to basically get the diameter and the stroke of compressor piston and the expander piston also in this case. And also I will get a phase angle which is basically the volume variations the phase angle between the compressor and expansions volume variation. So, first thing I will go to the temperature entropy diagram of nitrogen in order to calculate the cooling effect required or Q e required in this case. So, consider T s diagram of nitrogen as shown in this figure it is important to note that the energy required to condense nitrogen involves sensible heat from 300 key to 77 I have to now decrease the heat or decrease the gas temperature from 300 Kelvin which is my this point at 1 bar come down to 77 Kelvin over here which is my sensible cooling and then I have to cool the gas in the latent part and therefore, latent heat of vaporization at 77.2 Kelvin. So, how much energy do I require in order to get from 300 Kelvin at 1 bar to 77.2 Kelvin at 1 bar and then take out the latent part of it. So, that I get liquid nitrogen at 1 bar at 77.2 Kelvin this is the minimum heat I have to remove from nitrogen gas in order to reach to saturated liquid region at 77.2 Kelvin. Now, what is most important is in order to get 10 liter per hour of liquid nitrogen what is my mass flow rate.  So, from the standard T s diagram for nitrogen the change in enthalpy of these processes are the sensible heat from 300 to 77 Kelvin which is 237.7. So, H at 300 Kelvin and H at 77 Kelvin this is my difference delta H s 231.7 plus the latent heat which is going to be 199.1 kilojoules per kg Kelvin I will add this the net change in the enthalpy therefore, is 430.8 kilojoule per kg Kelvin this is my enthalpy change from 300 Kelvin 1 bar to 77 Kelvin 1 bar at saturated liquid condition. The required capacity of the given liquefier is 10 liter per hour the density of liquid nitrogen is 808 kg per meter cube. Hence, the required mass flow rate across the liquefier corresponding to 10 liter per hour is calculated as mass flow rate is going to be given by what is my n value that is meter cube per hour into density divided by 360. So, convert my 10 liter requirement into meter cube which is going to be 10 into 10 to the power minus 3 into density of liquid nitrogen 808 at 1 bar divided by 3600 which is giving me 0.00224 kg per second this is kg per second. So, the net cooling effect required to produce 10 liter of liquid nitrogen per hour is Q e required is going to be delta H we just calculated per kg earlier multiplied by how much kg per second my flow rate will be which is going to be this which will amount to 965 watts. So, my Q e required to get 10 liters of liquid nitrogen at 1 bar is equal to 965 watts this is my Q e required. Therefore, Q e design at 77 Kelvin is going to be 3 times this value. So, Q e design is going to be 3 times 965 which is nothing but 2895 watt what does it mean? I am going to design a cryocooler now for 2895 watt assuming that so many watts will be lost as losses in order to deliver 965 watts as cooling power at 77 Kelvin alright. So, my net loss assume will be 2895 minus 965 this is the loss and what is delivered is 965 watts which are responsible to produce 10 liters of liquid nitrogen at 77.2 Kelvin. Now in order to design this cryocooler I will now refer to the Walker charts over here which will give me Q max alpha and K which is what we just saw at different temperatures. So, first thing I will do basically is to locate the line of Te is equal to 77.2 Kelvin. Also what is known to me is the rp of the system is 1440 and therefore, rps or how many hertz are there which is 24 hertz 1440 divided by 60 this is my in order to calculate how much Q e design per unit cycle will be. So, Q e design per unit cycle is therefore, will be equal to 2895 divided by 24 which is equal to 120.6 and this is Q e design is used to calculate my Q max now alright. So, this is my Q e design per unit cycle. So, let us go to the optimizer chart and let us draw a vertical line from 77.2 Kelvin at which cooling effect is going to be produced and the first iteration we can assume that x is equal to 1 from Walker chart and we can see that for x is equal to 1 I will get different values. So, I get K is equal to 2.85 from here I get alpha is equal to 0.575 radians which is equal to 32.9 degree. Now, this is not a very happy I mean as we just saw that it should be between 60 to 120, but this is our first iteration and we are getting value of alpha to be 32.9 if you want I can increase my value or decrease my value of x so that I will end up in whatever alpha I normally would like to have and the corresponding the value of Q max is going to be 0.07 which is located from this curve and all these values have been taken at x is equal to 1 and T is equal to 77.2 Kelvin. From the definition of Q max now I get Q max is equal to Q e design upon P max by V t and we already calculate my Q Q e design we already know what my P max should be because the problem defines that P max should not be more than 40 bar and I know Q max which means I will get the value of V t from this particular expression P max is equal to 40 bar and therefore V t equal to Q e design which is 120.6 divided by Q max which is 0.07 into 40 bar to be converted into 40 to the power into 10 to the power of 5 in order to get millimeter if I want to have a meter over here from here I get V t to be equal to 4.3 into 10 to the power minus 4 meter Q that means I got a total swept volume V c plus V e compression space volume plus expansion space volume as this particular quantity which is nothing but 430 cc now I know k again here which is 2.85 from this particular expression from this particular graph V c by V equal to 2.5 what I know V c plus V e equal to 430 cc and therefore I can calculate the two volumes and this is nothing but V e is equal to 112 into 10 to the power minus 4 meter cube which is nothing but 112 cc 112 cc and again I got V c which is 3.18 10 to the power minus 4 meter cube which is nothing but 318 cc so that means I know now compression space volume expansion space volume in meter cubes and I can now calculate what should be corresponding diameter and the stroke of the piston and the displacer for the unit for which we are designing this is a cryopolar. Assuming now stroke to bore ratio of 0.75 for both compressor and expander pistons we have the following we got a V c equal to pi by 4 into dc square into stroke of the piston and therefore we know what my V c is which will give me the value of sc by dc has been assumed to be 0.6 0.75 correspondingly I can calculate my diameter of the piston to be equal to 81.4 millimeter and the stroke of the piston to be 60.8 millimeter similarly I know value of V e which is pi by 4 into d e square into s e in fact expander piston that is what I should call it here because it is not a displacer in this case s e upon d 0.75 which is an assumption I get d e as points diameter of the piston for the expansion side is 57.5 and stroke is 43.1 millimeter. These are my first guess dimension if I am not very happy about this I can go back to my TMSN chart for example this dimension can come very large depending on for which capacity you are designing this cooler and if you find it impractical to have such fabrication or such space allocation I can as well go back change my value of x for example or you can also change your Pmax required in that case for example if Pmax required is going to be smaller quantity all these values are going to be very large if I allow my maximum pressure to be higher side then my dimensions might come down on the lower side and this is where you have to do iterative exercise. So, this tutorial gives me for this compressor expander arrangement dc equal to 81.4 as given over here sc or the stroke to be 60.8 millimeter as given over here similarly diameter of the expander is given as 57.5 and stroke is given as 43.1 millimeter. So, my operating parameters and the design parameters are given as the operating parameters are Te is equal to 77.2 Kelvin Tc is 300 Kelvin Pmax is 40 bar and n is equal to 1440 revolutions per minute similarly for design parameters I got vc ve and alpha as 0.75 radiance which is equal to 32.9 degrees. So, these are my first guess I am not going to be iterating over here what the point I want to come across I want to give as if these dimensions you find are on a very higher side for example this is for a 10 liter per hour, but tomorrow if I want to you design for 15 liter per hour and I say that the maximum pressure should not exceed 30 bar in that case these dimensions can come very large and in that case you may find that one compressor piston is not enough and you may have to go for two cylinder system or you may have to go for four cylinder system depending on capacity you are talking about for example a 50 liter per hour cryocooler may have four cylinders alright that means each cylinder will give around 12.5 liters per hour accordingly decision has to be taken to determine what my diameters and what my strokes should be alright what my maximum pressure should be what my x value should be and this will determine the diameters and strokes of the piston and a displacer or the expander and the compressor respectively. So, here you have to take a call how many iteration would you like to do is P max is equal to 40 bar is enough if not can it be higher if it is on a higher side these dimensions can still be reduced because comparatively for a given max my vc or ve will get reduced for a higher pressures and therefore this can be considered on a lower side it also depends on how much area is available for your cryocooler if the space available is going to be smaller and smaller then you might allow it to go for a higher pressures in that case however the parameter which are not being considered over here is the mechanical design it should stand the mechanical design that may diameter the thicknesses etcetera should be able to stand all these stresses generated because of this higher pressure what we are doing going to do is only a first case based on the thermal design the thermal aspects of the system alright. So, what we see for a given qe design if the dimensions of the piston and displacer are going to be very very large say more than 150 millimeter the system may be designed for two cylinder in that case this is what I just said earlier alright. So, this is an iterative process until the feasible dimensions are decided. So, you can play with operating parameters like maximum pressures cooling effect requirement the factor of safety which we have taken is 3 times q required it could be 4 times qe required it could be 2.5 times qe required again the data volume ratio as I said x has been taken as 1 you can reduce this to x equal to 0.8 this also will make an impact on overall design of the system. So, this has to be done therefore in a iterative manner what we have just shown is one iteration what we have just shown you how do we calculate these parameters all dimensions for a design of a cryocooler of 10 liter capacity. So, you should try different version of 5 liter 8 liter 15 liters and so on the conclusions that are drawn from these lectures are for an optimum design of cryocooler a compromise between the operating and the design parameters may be sought as I said that can I increase the maximum pressure the design parameters will be different in that case alright can I increase the data volume the design parameters will be different in that case also which we saw that with the increase in the value of te the q max increases w max decreases and c o p therefore increases with the increase in the step problem to show k we found that q max and w max increases c o p will remain constant because c o p is a parameter which depends only on the tau as well as ideal sterling cycle is considered with the increase in the value of x q max and w max decrease in both the cases. The increase in the data volume leads to decrease in pressure ratio and pressure drop q max and w max curve for phase angle variation pass through a maxima the curve get flattened near the maxima close to 60 to 120 degrees. So, as far as possible you may would like to have a value of alpha between 60 to 120 degrees if allowed a combined effect of parameters on the performance of system as a whole is given by walkers design chart. So, this is the first level optimization chart which combines various operating and design parameters and therefore, can be used for first guess dimensions for a realistic analysis we have taken q e design equal to 3 times q e required this is where 3 is basically acting like a factor of safety it can be taken as 2.5 or 3 or 4 or whatever design conservative design one would like to design for. And lastly we have been an assignment for a 15 liter design of an hydrogen like for a 15 liter system the steps have been given you can have x is equal to 0.5 for the design procedure and go ahead for design calculations. Thank you very much.


What's going on guys welcome to another vlog today? I'm actually at by one of the school buildings right now, so funny story today. I actually I have two classes today People trying to have on bikes here at school. It's just Well anyways, I got two classes today, and I had one at eight o'clock to 1030 and I had one out of 11 to 130 well I Woke up this morning pretty early took a shower I sat down played on my phone for a little bit checked on social media checked emails checked stuff like that I was like, you know what? I'm gonna just close my eyes for a minute. Well, that did not work. I Woke up around like 830 and you know, I was just like I might as well skip the whole day now And so I'm not I'm not really worried about I mean the first class kind of wanted to go to but our last classes I presented both my projects one and each so it's like we're just starting something new But actually my second class I finished the project that she's about to show the class like I was ahead on work I asked her if I could start the new project and I already did it so I'm already done for that. So I'm not worried about that at all but I'm actually going to the boat storage right now why not use my day to like clean up the boat and get everything organized because Man, I've never seen my boat so dirty in my life. It's so I can't take it anymore It's freaking me out my truck's dirty. I might even get my truck wash today. I was just thinking about that so Yeah, headed the boat storage right now gonna clean it up gonna take you guys along with me Let's get started. Oh Just got the boat storage. I'm really I'm gonna clean up my boat. I wiped it down a little bit yesterday But it was so filthy. I can't take it anymore. It looks a lot better like this top half I mean look at it looks clean Because I was cleaning it yesterday some but then when you look I wiped some of it off a little bit. See that line That's how bad it is. I mean look that's horrible. That's from the river, but look how clean I got this I mean, I didn't spend too much time on it either Let's kind of start wiping it down Turned out pretty good, but I really need to clean out some of the inside as well clean clean clean dirty See that's how it was all over the boat. I'm talking. It was bad.  I like Mary that we go to it has a lot of this nasty grass.   This thing is filthy some probably filthiest. I've seen my truck I've just been going out on the river and everything, you know, and it's just when I park at school I park and gravel lots 90% of the time and it's just it really dirties up my truck Which I hate Grab these Some cleaner. Let's do a quick little detail on it. I'm not gonna fool out wash it So I don't really have an area to do that right now And if I bring my boat out here I actually behind this place is a big old gravel lot and that gravel lot is just gonna dirty That's like 90% of the reason why my truck and boat are so dirty is because we're putting them in over here It just gets you know There's all those truckers drive through all that stuff and just kind of like splashes it all over my truck and boat Even with the garage door open with my boat showing it's gonna get some crap on it before I even start cleaning stuff I just like to say I believe this is what you guys like Like these type of videos drop a comment below leave a like This is what you like just let me know because I want to know and Because I feel like this is a type of videos that you guys like well I actually posted the tournament preparation bass push-off vlog Preparing for the tournament getting baits at the best push-offs. You guys love that.  I could tell because it got three times as many views as my other videos within the first You know eight hours, which is absolutely amazing and if that's what you guys like I'm gonna post more of them So I want to know so leave a comment below like the video if this is the style of videos that you guys like And if you guys haven't already hit the bell by the button subscribe button hit the bell So it notifies you about all my uploads rather than that. Let's go ahead and start this thing. I mean, I'm kind of I'm not really feeling it right now, but I'm feeling like filming. I'm in the mood to like vlog I'm in the mood to film. I got you to be so let's let's go ahead and just let's just polish this baby Let's give him clean This rag Definitely going in the trash after all this. How does that baby clean now? I still haven't got that console Tyre just ignore that, but they're otherwise. Oh, it's just It's really Really clean not too bad down here except Boy, no good Happens to me every time Good, but uh, just wait. This is even worse. Yep This is why I'm cleaning out my boat Absolutely, there's one empty bag. This is all the rivers pin lately I have like 20 empty bags in here somewhere I don't know they're in here somewhere.  So now I got literally a thousand red trinkets and dirty water trinkets This was talking about about the bags of stuff That's empty. You think I I mean look at this This is just the past like two that was past week or something.  That's not bad. They're chewing Geez, I think it's fair to say that the middle compartment is pretty clean and good to go I have a lot of baits in this bag that I'm gonna have to deal with another time and start putting them in boxes You know figuring out what I'm gonna do, but that's for another time But overall, I mean it's pretty clean got all that trash out Way in bad. I need to put that in the back corner Suits life jackets need to go in these two And honestly, we're looking pretty solid overall the boat is pretty clean rather than that, but I'm gonna get to that later That's gonna be off Apartments clean now. I just have to wipe all this off See if I can get all this off pretty clean You can do it. Oh, yeah, there we go. Look at that compare One wipe. Does that even compare? Ridiculous Gosh, it's looking good. It feels so much better.  Oh Cleaned up compartments cleaned up just gotta get a few baits put away, but rather than that I mean this thing's this thing's pretty clean for right now. I couldn't like get a hands-on wash But it's alright, you know, it's wiped down everything looks clean and good Great and presentable. Well guys, hope you guys enjoyed this video This is something new I want to do, you know I want to do stuff like this cleaning my boat clean my boat out, you know boat tour truck tour That's coming soon this summer because once I go home and we get everything cleaned up really good Do a boat and truck tour and I get everything rolling But overall thank you guys so much for watching if you enjoyed this video Be sure to hit the thumbs up button Be sure to leave a comment below if you guys like these type of videos and just let me know because this is the Type of stuff I want to do and this is type of stuff I believe that you guys like and I want to know if you guys really like it so I can start uploading content like this But overall thank you guys so much for watching. Please hit the like button Please subscribe and leave a comment below. I'll catch you guys the next one


Okay, he's alright, he's alright. Anyway, so it's about that time where we play the game. So, karibia, karibia. And today's challenge is, me I don't like, I don't like this. This one is going to be one of my favorite games to play. Yes, because you chose it. Yes, this one, he nimi mi nilingia now. You see, like how people take shots. I know most of you men in the club will have to take shots. Some of them will have to take a big shot.  Ya, konyagi. Ya, konyagi. No, something. Ya, kali kali. No, not top notch. Like chikila or something.  So what you're going to do is, we have lemon, we have ginger, we have pepper, pepper nipili pili. So, lazmo ume. Zodani beta. So lazmo ume and you have to keep a straight face. If you don't, you lose. So I think since last Saturday fell us in New Orleans and ladies in Malaysia. We're going to start with the ladies, are we going to start with the easy one? No, we're not starting with the easy one. Let us just start with the hard one. Dutumali nilingia kwa at least tangu ki dogo. Chwa takai u kali diwata i baki kwa mudo mo bende temu na mazah game uta kwa like hmm. So ladies first. The flow is all just. Hazana nandimu, dimu ndimu ndimu ndimu ndimu ndimu ndimu ndimu ndimu ndimu ndimu ndimu ndimu ndimu ndimu ndimu ndimu ndimu. And you have to bite, like actually bite it. Bite and I'll take the juice. Adiyo machungu ake na kwa maganda ake na kwa ga kali. Here we go. I am making maganda nengumu. Juice. I'll make face. I couldn't match up. So that is one. I'm not making face. She is? I have seeds in my mouth so I'm not making face. Meza hazita nia kwa tumbu ha. Ah, hazita nia kwa tumbu ha. Ah, hazita nia kwa tumbu ha. Your turn. Nani ya na reisi bumana. Isi ata siyo, isi yo lemoni n'nimu ndimu ndimu? Nningi lemon? Tulitu nini. Si kali sanda na. I actually it am. Kunazingine? Si kali sanda. That's cool. I am. Next one? Pili pili. Ikali gulu ko pili pili. Like ginga nikali gulu ko pili? Ginger, si kali. Okay, I'll try ginger then.  Kusho bachu zi toki Ha, aiza actually red Amani 420 labda Inya That's one one You make a straight face, you scared Aya He's on you Goja, goja Okay So on to my favorite one Yapan ajotunda luz rosas Ya kabusi oge Ladies first So sir, easy taribut Trust you me The taste in my mouth right now And then kutane na pili pili Yes, and you know Nambadu, na umesahao Itna kwa gata mwikingi Nambadu na kwa gana storyingi Fani nafmi sijai fili I only feel it Nida umana tumba, I will feel it But we are not biting, me I am just biting No, it's like a half No, it's not a half, a quarter Kula half, pepa ya buwana Mama kadoa ga buwana Chikenye me umuwa Bado ni kali And I have not made a face Sijawa eka face Aja Inkosao Tama kananda za red in Diokali Diokali Rata tuon Miriam pala kwa kamera kwa like to Yari she is cringing at everything that we do Ya, am good No, no ma tu dogo buwan The after effect of my friend, let me tell you You make a straight face aje I think the next one you need, kwenyagi and tequila I don't like this I have a punch, this is making a face so Can we Ya dilkwa na juiz Ya ya ya One of my favorite games but once, instantly Let me tell you what I do At least in the middle of your life This is a bad one If you want me to give you juice Can you get some milk? You see Whenever DJ Nesh can choose We have to suffer We have to suffer It's good for the fans It's good for the fans but we are suffering Very soon we are going to invite one of our biggest fans To play one of these games I am sorry, ma chozi na muwagi Kahe buwata mi niye da pakanda kwa dog Can we get music while we are suffering We are hurting over here


I'm going to talk about robots, but a particular subclass of robots called soft robots. And the question you can ask is, what are they? And I'll tell you something about that. The more important question is, who cares what they are? Something about robotics, generally. And there are several people in the audience who know more about this than I do because I'm a professor that doesn't deter me at all from talking about the subject. And then I'm not going to talk about that at all. So let me start, generally, with the subject of robotics. A little background of what is that. Those are gold coins. There was once a time when nations competed for wealth in the form of natural resources, gold, land, whatever it might be. And the world has changed. And now what nations compete for is basically skilled people, information, technology, and knowledge. And that's terrific. So there's a competition. And what's the competition really about? And I think one can argue that when you think about the competition between US, Europe, and China or US, Europe, and India, what we're really competing for is none of the above, but we're competing for jobs. And more than jobs, we're competing for good jobs. And what does that have to do with anything? Well, this is often phrased in terms of high wage versus low wage kinds of jobs. That's that's gone because the wage differences are not much different now. Skilled versus unskilled, where you find skilled people everywhere, but this is the part that I think has to be interesting. And that is, what about a world in which it's not people competing with people, but people competing with machines for jobs? And that's robotics. And that problem can be phrased in one of two ways. It can be either people versus machines or people with machines. That is, machines that augment the capability of people. And the new element in this, I would argue, and many people would argue, is robots. And there are lots of folks who will say that if you ask, what's the next big thing after the web? The next big thing after the web, arguably, is machines that begin to rival people in their competence. So these are just pictures of certain kinds of machines, robots you're familiar with. This is an assembly line. This is a drone. This is the Roomba, which is the world's least successful method of cleaning floors. This is a surgical robot, which is one of the world's most successful methods of increasing billing rates for procedures. This is Mars Rover. And I'm going to show you some things here, which come from the military, who has done a lot of this. Now, there's a word you need to know. When you go to cocktail parties, it's important to know certain words, because you can use them and you appear to be an expert, even if you know nothing about the subject. And one of them is cooperative and non-cooperative, as in robotics. And a cooperative robot is one that works with people safely, and a non-cooperative robot does not. Let me show you an example of a non-cooperative robot from, this is from Boston Dynamics, which is a company that does this kind of thing very well. The sound needs to be up, because it's disappeared. There we go. So this is the tether. That's a concrete block. And this is not what you want as a babysitter. And I want you to look at the next, I think it's the next one that's really the thing that's interesting. Look at the beautiful way in which this balances. Shifts its weight as this center of mass moves. It controls itself. And the thing that you need to understand is it does all of that without a brain. This is just gyros and accelerometers and local feedback loops and things of this sort. I can't tell that that's not alive. Now, it's tethered, and there are things like that. But its balance is so terrific. So the interesting question now is you take mechanical systems that are rapidly beginning to equal animals in certain aspects of their performance. This is the biomimetic part that we're talking about. And add to it artificial intelligence. And I see no reason why we shouldn't have things that are the functional equivalent in 10 years of a cat.  So this is not a great claim to something or other. But nonetheless, it's really important. All right, so now what are soft robotics? Soft robotics, if you looked at that thing through the concrete block, it's all metal pieces. You don't want to get in the way of it. It really doesn't know that you're there. So soft robots are robots that are designed in such a fashion that they move. They do stuff mechanically, but they do it in a way which enables them to work cooperatively with people. And this program started here. And you say, we've gone off track. How can soft robots start with a coke can? The answer is the problem that we were posed, in this case, or the problem we posed to ourselves with DARPA, was to make something that started looking like a coke can and unfolded and could walk across the floor, find a crack under the door, crawl under it, and reconstitute itself on the other side so it didn't look like a coke can. This is not a specific problem that I happened to be interested in, but you can imagine why somebody else might be. And what is our inspiration for this? And this is where soft comes in. This is a soft animal to act as our source of inspiration. One of my favorite creatures, it is a octopus. I particularly like to eat them. And the reason for that is that I have an ideological belief that one should only eat things that are more intelligent than you are. And this qualifies. But look at the way it's pulling itself through this very small hole. I can't do that, and I'm going all the way to the end because there's a little bit at the end that I particularly like. I don't actually know what portion of its anatomy that is, but the brain is plastic, and it's somewhere up in there. But look at the look of intense self-satisfaction on this. So this is where we started. And those of you who are in the robotics business will recognize there's something interesting here. And this is an uncooked egg. This is modeled very loosely on a starfish. And the problem of picking up an egg is not a trivial problem, because if you're doing it with hard grippers, you have to have sensors. You have to have feedback loops. You have to do a series of things of this sort. What we have here is simply a inflatable structure that I'll show you in a moment. That's the suspension element. And here's a single pneumatic input line. And so when this structure comes down and grips the egg, it cannot apply pressure at any point on the egg that is larger than the pressure that you use as an input, hence as self-adapting, hence the properties of materials have taken over from the usual control feedback systems that you find in most robots. How has it made simplicity itself? One has a structure which has the characteristic that there is a flexible but non-extensible element here and then inflatable element here. As you blow up this, the system has to bend. And that's what's going on here. And I'll show you some complexities of this, but that's the basic idea. Now, there are some things that I just want to sketch for you. Here is a picture of the structure. It's a series of little bladders that are connected by a network of channels. But if you look at this system flexing, you notice something very interesting, if you look carefully, which is it starts from the tip. And that element of starting from the tip could be done in more complex mechanical systems, but would require a lot of control to do. Here it occurs naturally because this is an example of a non-linearity in a material system called, in this case, snap-through. And there are many ways in which you can build properties of materials in such a fashion into these systems that they replace control systems. How's it done? Simplicity itself, you build a 3D mold using a 3D printer. You mold an elastomeric plastic in this, and then you simply glue stuff together. And I'll show you how it's done in earnest a little bit later. But the polymer that you use here is the same one that's used for facial implants and breast replacements and things of that sort. So it is quite soft and quite elastic. Now, you can also get fairly rapid response. And these are systems that, in this case, are still a long way from the apostionata, but they're moving in that direction. But they have about 100 millisecond response times. And I'll show you an application of that in a bit. And then you can move to systems of this kind, which is the first stage in the Coke Can story. This is a system that has one, two, three, four, five bladders. Here is the pneumatic tube that underlies it. Here is the bottom of our hypothetical door. It's a glass frame here. And there's a certain poignancy in this whole video. People, when they see these things, say, oh, that's really neat. It's almost alive, but it's really creepy. And so what it's going to do is work its way under here. And a point of interest in this is that it has, in this case, show two gates. One is one in which it's erect, which we call walking. And this particular gate, which we call uching, because that's a highly technical term. And it will make its way under this. And then it will stand erect again and do whatever it's doing. There's no reason to go through the entire business, but you get the idea. Now, let me show you a couple of things that are interesting about this, this class of things. And I'm just really sketching. This is something that you've seen before. But this is a model for a hand. By modifications to the structure, it's possible to build in features that look a little bit like knuckles. And one of the neat things you can do here is to ask questions about biomimetic systems.  You can make all of those structures very easily and test their ability to do things. And that's quite interesting. But there is another thing that you can do which illustrates one reason why these are attractive as a complement to what's been done in classical robotics. That's a hammer. This is our little robotic hand. And so we whack it. And at least my response to this is always to say ouch. And to show you that this is real, it's real. But if you did that with a small hard robot, you'd smash it. These things almost can't be broken. You think they can be cut, which hard robots can't. But you can throw them off a building and it turns out their terminal velocity is not enough to break them on impact. So what can you do with that kind of thing? And here's an example. This is basically a Sears and Roboc glove, a department store glove, with these fingers that I showed you playing the piano put on the outside. And why does anyone care about that? And the answer is that this is an example of one of the large areas of application of this which is in surgery and rehabilitation. The particular problem here is that if you have a hand and you have stroke then it's really important to manipulate the hand otherwise you develop spasticity. And that's presently done. The manipulation is done with a nurse who is expensive and gets bored at the process. So if you have this kind of thing, what you do is you simply, there's my cursor. This will do any sort of manipulation you want in a way that's very compatible with human beings and also very inexpensive. And so there's an opportunity to do all sorts of things in which these actuator systems work cooperatively with people. And these are simply examples of some applications. So in addition to flexing, you can use this sort of system in many variants on it to increase the strength of the grip or to give you greater dexterity or to do things of that sort, which you can't do if for one or another reason you have a neurological problem or a stroke or something of that kind. And these are really proving to be very interesting and useful. Now, just one small issue in this subject. And I want to return just so that you can look at this.  But if you ask what's happening here, what happens and what causes these to curl from the end is that the first thing to blow up at the end, the very tip there, is the chamber that has nothing on one side. So that blows up. When that blows up mechanically, the next easiest thing to blow up is the one that's next to it.  It's very hard to blow at the very beginning, but then it forms a bulge somewhere. And as soon as it forms a bulge, that bulge propagates. It's exactly the same phenomenon. But one of the real attractions of this kind of biomimetic structure is that it gives you the opportunity to take advantage of the nonlinearities in materials to do things that you really couldn't do otherwise. And here is an example of one of our current models. This is, as you can tell, a spider. Spiders are pretty interesting creatures for all sorts of reasons, but one of them is that much of their actuation comes from the way in which they handle these joints and the mechanics of those joints. And I'm not going to show you the details, but again, but it's another simple pneumatic system in that case run by a fluidic system. And one can easily model, not easily, but one can model those kinds of systems. And what you see there is a thing which has six legs like an ant, but it uses the same joint actuation and movement system that a spider does. And that particular one is made out of sodas straws, the kind of thing that children use with some other stuff. But you can also do more elaborate things, and here is water strider. And this is actually pretty much the way a water strider works. It supports itself on four legs and then it has two legs that scull. It has to have hydrophobic patches so that it stays on the surface and it has to have characteristics that enable it to not sink. And this is lightweight, can be made hydrophobic and you can manipulate those arms as it does, more or less. Now I want to show you briefly one last set of videos. And the idea here, at least I hope, let's see if I can get these two plodding, here we are. The idea here is that one of the things, particularly if one is talking about the developing world, one of the things one would like to do is to find science that leads to technology that leads to jobs, goods and services relatively rapidly. And what's been so interesting to me about this is that our first paper in this was published in 2011. In 2013, we started a company which is called Soft Robots. I have had nothing to do particularly with that, but they have gone off and looked at grippers. And I want to show you what good industrial engineers can do with this kind of thing. One of the questions that came up was, can you lift a weight? And there is this kind of gripper lifting weight. Potato chips are actually hard to pick up because you tend to pick them up in a way with hard grippers that they either have to have elaborate controls or you have to do something that enables you to avoid crushing. Picking fruit is an interesting thing that requires delicacy, picking up this cup and then the task we all face every morning of picking up a cactus. But I'll show you just one other brief section of this. Oh, this is very important and those of you will recognize it. This is dexterity and there's a neat example of dexterity right here where one has a ping-pong ball and you reach around and you manipulate the ping-pong ball. Notice this is on the end of a conventional robotic arm but it catches the ping-pong ball quite successfully and I think this video, you know, this is something slightly different but that's something else which is pretty hard to do. Here, this is interesting. For these end effectors, what one is always going to have probably is a hard arm and you have to change the fingers and you just saw that system change from three fingers to four fingers. It is very easy to do so that what one will have is an arm and then a tray of different kinds of effectors and the system will go from one to another. Now that gives you a sense for where things did this. One last slide or maybe two, one last slide here. Who did it? And a lot of what one thinks about what one thinks about new areas is do you have to have a synchrotron or do you have to have a light source or do you have to have something like that? And I hope you've gotten the sense that the work that's involved here actually involves not much more than very simple ideas in mechanics plus simple polymer chemistry and molding. But what interested me was that if I look at the group of people who've migrated to this, a couple from the US but only a couple and then Spanish, Singaporeese, Italian, Chinese, German, Canadian, several Iranian students, they're very good. Several Turkish students, very good, Chinese, Canadian. It turns out that everybody is interested in this and almost everyone is able to do it. So it is a technology that is both scientifically interesting but also technologically very useful in which the barrier to entry is very low and that I think is relevant to this particular meeting. So then let me use one last slide to summarize. I said that I would tell you what soft robotics are. I have, they're soft, they're robots. It's not too difficult. What are they going to be used for? And the answer to that is I think that at least initially they're going to be used for tasks that hard robots cannot do. And the wonderful thing about a biomimetic study is that if you think about all the organisms out there, insects and single cell organisms and dual flagella, algae and animals and birds and whatever, they're a very, very large number of biologically successful architectures to model. I emphasize that what we've done here has nothing to do with the mechanism by which biological organisms work. It has to do only with mimicking the function or motion and that turns out to be a much easier thing to do. But what it opens is the door for robotic systems that have the characteristic that they can operate safely and cooperatively in contact with people which has been a barrier which has been a little bit difficult to get over. So collaboration is very important. Another very important thing is cost because these things basically don't cost anything. That again is something which is available to all levels of economy. And it has the interesting characteristic that for some of the planned applications as in search and rescue think Fukushima. You would like to have something that could crawl over rubble in water in a high radiation environment, see what's in there.  Same thing in a burning building. And you don't want to do this with a 50 to $100,000 hard robot but you would have no trouble abandoning one of these little rubbery things. And then applications, we are a group that is very interested in applications because I think they focus the mind and the students like them a lot. So what are we going to be doing? Here are some surgery I've mentioned, surgery and rehab and prostheses, obvious for cooperative systems. Agriculture and the issue here is to take humans away from jobs that are really hard physically and tedious. Search and rescue I've mentioned as in single use, hazardous tasks. But interestingly the one that turns out to be the really big deal is gripping. And you say who cares? And the answer is Amazon. Because if you look at these big end-of-chain consumer product stores you write in or you type into your computer the idea that you would like to have a can of lube oil and some potato chips and whatever you happen to be interested in. And it turns out to be very difficult to find a non-human system that will pick all these things up and put them in the box. These have the characteristic that they can do whatever you want.  You go back to, let me, I'll find it again. You go back to the example which was this, which is what the industrial engineers came up with with their solutions. And the point I'd like to make about this is that what you see there started with the idea of a starfish but actually there's no biological system that looks like that. So one of the interests and charms in this to me is that you end up working from something that is a natural structure that has been successful in a Darwinian sense but you may well arrive at solutions to problems that are I think only vaguely based on those biological issues. That is the final answer may be quite a different answer. And so in this particular case, what you see is something that has fingers but so far as I know there is no biological system that operates in this fashion. So it's a very entertaining area is one that spans from observation of nature to production of technology. It is, it turns out really easy to do and there are now a gazillion people doing this kind of stuff. And it looks to me like it's going to both lead to good mechanics, good robotics, interesting problems in control and materials and technology that can be used for a wide variety of purposes. And I'm done on time. Thanks for coming up.