At the end of March, we attended the ARPA-E Energy Innovation Summit in National Harbor, MD. At the Summit we presented our work on power electronics tailored for fusion systems under an ARPA-E GAMOW grant. It was a great experience to network with many other awardees of ARPA-E grants working on innovative energy projects and learn about the power electronics needs of potential customers so we could design our boards to these specifications. Shown below is our Summit booth which was run by PSS Mike Paluszek and me.
Breakout sessions included panels on: future plans for inertial fusion energy, nuclear & materials, rethinking the nuclear waste challenge, and scaling up innovations for impact in the private sector with the ARPA-E SCALEUP program. Dr. Neil deGrasse Tyson gave a talk at the Summit!
The pdfs of the trifold and posters at our Summit booth are shown below. If you have any power electronics requirements for your systems, please contact us at info@princetonfusionsystems.com!
Stephanie and I attended the YWC conducted by PPPL at Princeton University on March 16, 2023. This conference introduces middle-school and high-school-aged girls (in 7th to 10th grades) to women scientists and engineers and the wide breadth of careers available to them in these fields. Prominent women scientists and engineers from around the region spend the day with the girls engaging them in different variety of formats that include small-group presentations, hands-on activities, a keynote address, and a chemistry demo. This event is a great motivation for the girls to choose STEAM as their career.
We had 3D printed models of the Princeton Field reversed Configuration (PFRC), a Poster of Direct fusion drive, Spectroscopy diagnostic poster that demonstrated the visible and X-ray diagnostics that are performed to predict the electron temperature, impurities, and how these vary with other experimental parameters such as pressure, magnetic field and RMF-heated power in PFRC.
I demonstrated how visible light can be split into different wavelengths using a hand-held spectroscope. Visible light waves are electromagnetic waves. We see these waves as the colors of the rainbow. Each color has a different wavelength. Red has the longest wavelength, and violet has the shortest wavelength. These different colors of waves together make white light. The girls enjoyed observing different wavelength colors using the handheld spectroscope It was fascinating to see around 800 students after the Pandemic for this conference.
Lastly, we enjoyed the keynote talk by Dr. Liz Hernandez-Matias. Sr. Educational Specialist, CienciaPR.
One of the biggest concerns people have with electric vehicles is charging. We’ve taken our Mach-E on two trips with different approaches to charging. Our experience is with a rear-wheel drive Mach-E with the extended range battery. Its EPA range is 303 miles.
The first was from Princeton to the Berkshires, then to Boston and then back to Princeton. The trips were made without any charging on the way. We used Level 2 chargers at our destinations. The Williams Inn, in Williamstown, had ChargePoint chargers, as did the Cambridge Marriott in Kendall Square in Cambridge, MA. At the Cambridge Marriott, there are ChargePoint chargers in the garage used by the valets. The valets are willing to plug your car in as long as you have a ChargePoint card.
The picture blow shows our current mileage.
The most recent trip was from Princeton to Pittsburgh. The one-way distance of 330 miles necessitated charging on the road. We used the Ford app, which showed two stops. We didn’t follow its plan. Instead, we broke the trip into two segments each way with one charging stop. Prior to the trip we tested the high power charging at a local EVGo station.
In both directions we stopped at the Electrify America charging station at 1098 Harrisburg Pike in Carlisle. It was only 2 miles from the highway at a location with the Sheetz convenience store. There were two 350 kW chargers and two 150 kW chargers. Here is the station on the way to Pittsburgh.
It took about 20 minutes to charge from 30% to 80%. We charged until Apple Maps said we had 20% battery margin at our destination. In both directions we ended up with about 15% margin. In Pittsburgh we did destination charging at the Forbes Tower garage. The garage was $22 for 24 hours and charging was free. It was a short walk from the Residence Inn.
On the way to Pittsburgh we were joined at the charging station by two Ford F-150 Lightning trucks. On the way back, we were joined by another Mach-E.
The Electrify America stations were seamless. We have 250 kWh of free charging from Ford. The station knew all about the free charging and we didn’t have to pay or do anything else to be reimbursed. It was simply plug and charge.
PlugShare was the most reliable way to find charging stations.
We drove a Tesla Model 3 as a Hertz rental In Chicago. We charged once at a SuperCharger. It worked very well! I’d say the Electrify America experience was its equal.
At MIT, we are given the month of January off from classes to pursue our own interests, whether they be career-oriented or hobby-based. During these five weeks, I have worked at PSS as a power electronics intern. My time at PSS has given me the opportunity to explore so many of the industry based applications of electronics and electrical engineering amongst some of the most innovative minds in the aerospace and energy industries.
Within the GAMOW (Galvanizing Advances in Market-Aligned Fusion for an Overabundance of Watts) project, my work centered around helping redesign, assemble, and test a power load switch, the resulting prototype of which is shown above. Within this project, I received a wide array of experience ranging from 3D-modeling PCB boards with Eagle software, to physical board assembly, to designing testing procedures for the completed board. Initially, I worked on redesigning the load switch PCB to reduce loop currents and noise. My next steps were to source and order all needed components for in-house assembly. During the assembly process, I worked with both a soldering iron and hot air rework station to assemble surface mounted devices (SMDs) and through-hole components.
Raspberry Pi setup for PWM
I also dipped into some software based components of the project, programming in C and Python to create hardware based signals to our desired testing specifications. Specifically, I was aiming to make Pulse Width Modulation (PWM) signals of a specific duration for the Raspberry Pi to output. This led to various tests on the outputs of the code, through the use of an oscilloscope (two PWM pulses on the oscilloscope are shown below). Ultimately, I had the chance to start testing the board in connection with a power supply and the Raspberry Pi’s program.
Moreover, I had the opportunity to dip into so many different branches of electrical engineering and project design. In attending meetings about all of the individual components of the massive GAMOW project, I saw how the team plans and executes each individual collaborative part of the project. This experience in the project process and cutting edge electrical project design as a whole have given me many insights into the professional world of electrical engineering.
During my time at Princeton Satellite Systems, I worked on a momentum unloading project for NASA’s Gateway, a component of the Artemis program. I designed a deployable parasol that is controlled by Canadarm using Solidworks.
Solidworks is a platform I am familiar with, but I was still able to learn new functions. My favorite part of working with Solidworks is the puzzle-like nature of assemblies. When trying to make dynamic parts you have to think about how to best add relations without over-constricting or under-constricting the part. Once I finalized my initial design I was able to attend a Zoom meeting and present it to another company.
When not working on my Gateway project, I fiddled with the 3D printer to print models of the PFRC fusion reactor.
Although I have used 3D printers several times before, this time was more of a learning process. I was an acting 3D printer technician and wrote a guide with troubleshooting tips for future employees. Due to problematic unspooling and tangled filament the printer became jammed a few times, and I was unable to do the typical loading/unloading to set the filament free. This gave me the opportunity to take apart the 3D printer and see the internal mechanisms, which in turn allowed me to unjam the printer and solve the problem. I was thrilled to see inside the 3D printer and how the parts blend together!
Through my internship I learned about the complexity of the design process and how many things you need to consider when creating a product. Conceptualizing is one step, but bringing that concept into the real world requires much more research and planning. Overall, this internship was a great opportunity that allowed me to learn how to solve several engineering problems.
Our paper gives an overview of the Princeton Field-Reversed Configuration (PFRC) fusion reactor concept and includes the status of development, the proposed path toward a reactor, and the commercialization potential of a PFRC reactor.
The Journal of Fusion Energy features papers examining the development of thermonuclear fusion as a useful power source. It serves as a journal of record for publication of research results in the field. This journal provides a forum for discussion of broader policy and planning issues that play a crucial role in energy fusion programs.
Last week, I attended the American Physical Society Division of Plasma Physics (APS DPP) 2022 Meeting. As the name entails, it was a meeting full of plasma physics with applications ranging from astrophysics to nuclear fusion energy. There were many great talks and posters on plasma physics research by companies, national labs, and universities, and one could sense an overall feeling of excitement around fusion shared by many attendees.
I had a pleasant time in Spokane, WA. Pictures from outside of the conference center (with many conference attendees standing nearby), including the nice view from the conference center, are shown below.
I presented a talk on the Princeton Field-Reversed Configuration (PFRC) fusion reactor concept, and how we can leverage public-private partnerships for its development. The talk discussed technical details of the PFRC, including the past modeling and experiments, current investigation, and future research & development plans. The talk also described the markets and commercialization opportunities for this reactor concept, including disaster relief and asteroid deflection. Here I am at the podium speaking.
I also presented a poster on our recent investigations of x-ray diagnostics on the PFRC-2 experiment for electron temperature and density measurements, which was mounted on a poster board in the conference center. Many people came by to ask about my poster as well as about general PFRC questions, which kept me talking for the majority of the 3-hour poster block session! It was great to discuss ideas and results with many scientists and students at the conference.
Dr. Sangeeta Vinoth also had a poster at this conference on collisional-radiative model developments to extract electron temperature measurements from spectroscopy, which she presented virtually. APS DPP 2022 was an exciting conference to attend, and I’m looking forward to seeing updates from presenters at this conference. That also includes us, as we have more research and investigation to do — stay tuned!
This summer, I worked on creating a plasma circuit model as part of PSS’s work under the ARPA-E GAMOW grant. As part of this project, I wrote MATLAB functions to reproduce the results of two papers on impedance of radio frequency (RF)-driven circuits for plasma heating. Both functions take in some plasma and geometric parameters and return impedance values as well as plots of impedance as a function of other parameters.
The first function is based on reference [1], which uses the transformer model to describe the coupling between the plasma and the rest of the circuit. This means that the plasma can be represented as a resistor-inductor circuit that is inductively coupled with the main circuit. In addition to calculating the equivalent circuit impedance for values in passed-in density and frequency ranges, I reproduced the figures showing resistance/inductance and reflection coefficient as a function of the electron density of the plasma. Plotting over many orders of magnitude of density, you can see drastic changes in the plasma resistance and inductance.
Plasma resistance (solid lines) and inductance (dashed lines) as a function of electron density for five different frequencies, based on the transformer model in [1].
Since ion cyclotron resonance heating (ICRH) is a leading technique for plasma heating in fusion reactors, we also wanted a function that dealt specifically with ICRH in its plasma model. I then read through some literature on ICRH in order to find a suitable reference to model in MATLAB. I found this in reference [2], which became the basis for my second function. This model uses transmission line theory to calculate the antenna impedance with the effects of the plasma incorporated. This paper also compared a previously-formulated 2D model with its own 3D model, and the implications of this extension to three dimensions can be seen in the way impedance changes as a function of the wavenumber.
Antenna reactance (left) and resistance (right) as a function of the parallel wavenumber, based on the transmission line model in [2].
The impedance values produced from both of these models can be used to help account for the effect of plasma on antennas used in RF heating, especially ICRH. While assumptions are made in these models to allow for analytical calculations to be made (notably assuming uniform current density and neglecting volume propagation effects) and adjustments are needed to resolve minor discrepancies between the MATLAB models and the figures in the reference papers, they should be a reasonable first approximation of the physics that is occurring and the impedance generated by the plasma.
This summer has given me a lot more knowledge about plasma physics, in particular about resonance heating. I have also gained a lot of experience in conducting literature reviews, reproducing published results, and working in MATLAB.
[1] Nishida, K., et al., “Equivalent circuit of radio frequency-plasma with the transformer model.” Rev. Sci. Instrum. 85, 02B117 (2014); https://doi.org/10.1063/1.4832060.
[2] Bhatnagar, V.P., et al., “A 3-D analysis of the coupling characteristics of ion cyclotron resonance heating antennae.” Nucl. Fusion 22, 280 (1982); https://doi.org/10.1088/0029-5515/22/2/011.
Our latest textbook on MATLAB programming is now available from Apress. Practical MATLAB Deep Learning, A Projects-Based Approach, is in its second edition. It is available in both electronic and hard copy from SpringerLink.
New coauthor Eric Ham, a deep learning research specialist, joins Michael Paluszek and Stephanie Thomas. Mr. Ham led the development of a new chapter on generative modeling of music.
Harness the power of MATLAB for deep-learning challenges. Practical MATLAB Deep Learning, Second Edition, remains a one-of a-kind book that provides an introduction to deep learning and using MATLAB’s deep-learning toolboxes. In this book, you’ll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. This edition includes new and expanded projects, and covers generative deep learning and reinforcement learning.
Over the course of the book, you’ll learn to model complex systems and apply deep learning to problems in those areas. Applications include:
NEW: An aircraft that lands on Titan, the moon of Saturn, using reinforcement learning
NEW: Music creation using generative deep learning
NEW: Earth sensor processing for spacecraft
Aircraft navigation
MATLAB Bluetooth data acquisition applied to dance physics
Stock market prediction
Natural language processing
Plasma control
You will:
Explore deep learning using MATLAB and compare it to algorithms
Write a deep learning function in MATLAB and train it with examples
Last week, PSS Mike Paluszek visited ITER, the international fusion research experiment under construction in France. In light of Mike’s recent visit to ITER, we wanted to showcase an application of our tokamak Fusion Reactor Design function to the design of ITER. This function is part of the Fusion Energy Toolbox for MATLAB, a toolbox that includes a variety of physics and engineering tools for designing fusion reactors and studying plasma physics. We will also compute design parameters for ITER’s successor, the DEMOnstration power plant (DEMO), a fusion reactor currently in the design phase which is planned to achieve net electricity output.
We first apply the Fusion Reactor Design function to ITER. Note that ITER is expected to produce 500 Megawatts (500 MW) of fusion power, but this will not be converted into electric power, the power that goes into the electrical grid. DEMO, on the other hand, is planned to produce 500 MW of electric power from 2000 MW of fusion power. The Fusion Reactor Design function asks for the net electric power output of the reactor, P_E, as an input, so we generate a value for P_E for ITER by using the same ratio of electric-to-fusion power as in DEMO, giving us a P_E of 125 MW for ITER. The inputs used for the ITER design are shown below (see references [1,2]), where we use a data structure “d_ITER”:
d_ITER.a = 2; % plasma minor radius (m)
d_ITER.B_max = 13; % maximum magnetic field at the coils (T)
d_ITER.P_E = 125; % electric power output of the reactor (MW)
d_ITER.P_W = 0.57; % neutron wall loading (MW/m^2)
d_ITER.H = 1; % H-mode enhancement factor
d_ITER.consts.eta_T = 0.25; % thermal conversion efficiency
d_ITER.consts.T_bar = 8; % average ion temperature (keV)
d_ITER.consts.k = 1.7; % plasma elongation
d_ITER.consts.f_RP = 0.25; % recirculating power fraction
The first five inputs were described in our original post on the Fusion Reactor Design function. The function can be called to perform a parameter sweep over any of these inputs. We also specify values for some constants: the thermal conversion efficiency ‘eta_T’, the average ion temperature ‘T_bar’, the plasma elongation ‘k’, which is a measure of how elliptical the plasma cross-section is, and the recirculating power fraction ‘f_RP’. We can perform a parameter sweep over the minor radius (from a = 1.8 meters to a = 2.2 meters, with 100 points in between) and display a table of results simply with two lines of code:
d_ITER = FusionReactorDesign(d_ITER,'a',1.8,2.2,100); % run function
d_ITER.parameters % show table of resulting parameters
Looking at the results table from d_ITER.parameters, we see overall agreement with parameters for ITER [1,2]. The plasma major radius (essentially the tokamak radius) R_0 output is about 5 m, which is in the ballpark of the 6.2 m radius of ITER design, and the magnetic field at R_0 (on plasma axis) output is 4.8 Tesla, close to the ITER design value of 5.3 Tesla. The plasma current output is 17.5 MegaAmps, which is also close to ITER’s design of 15 MegaAmps.
The Fusion Reactor Design function also outputs plots that show whether or not the reactor satisfies key operational constraints for tokamaks, see the figure below. The first three curves check various constraints to ensure the plasma is stable, which we see are met as they are located in the unshaded region (though the green curve is marginally close to the constraint boundary). The blue curve’s position deep into the shaded region indicates that the reactor is far from producing enough electric current to sustain itself. The designers of ITER anticipated this, which is why ITER will additionally use a pulsed inductive current and test a combination of other techniques to drive the plasma current.
We now consider DEMO, which is in the design phase with the goal of net electrical power output. Similarly to running the ITER case, we set up a data structure (now called ‘d_DEMO’) with known DEMO input parameters [3] and perform a parameter sweep over the minor radius ranging from a = 2.7 meters to a = 3.1 meters:
d_DEMO.a = 2.9; % plasma minor radius (m)
d_DEMO.B_max = 13; % maximum magnetic field at the coils (T)
d_DEMO.P_E = 500; % electric power output of the reactor (MW)
d_DEMO.P_W = 1.04; % neutron wall loading (MW/m^2)
d_DEMO.H = 0.98; % H-mode enhancement factor
d_DEMO.consts.eta_T = 0.25; % thermal conversion efficiency
d_DEMO.consts.T_bar = 12.5; % average ion temperature (keV)
d_DEMO.consts.k = 1.65; % plasma elongation
d_DEMO.consts.f_RP = 0.25; % recirculating power fraction
d_DEMO = FusionReactorDesign(d_DEMO,'a',2.7,3.1,100); % run function
d_DEMO.parameters % show table of resulting parameters
The outputs for the DEMO case also show overall agreement with DEMO parameters [3]. The plasma major radius R_0 output is 7.8 m, which is not far from the 9 m design radius for DEMO. The resulting on-axis magnetic field output is 6.2 T, close to the 5.9 T of the DEMO design. The plasma current output is now 21 MegaAmps, which is less than 20% away from the design value of 18 MegaAmps. It is important to note that in each of these parameters, we see an increase going from ITER to DEMO, which is consistent both in our model’s output and the actual design parameters in the papers [1-3].
The operational constraints plot for DEMO is shown in the figure below. DEMO is a larger reactor than ITER, and given the favorable scaling of tokamak operation with size, we expect improved results for operational constraints in DEMO. The three curves which check plasma stability are all satisfied. Unlike in the case of ITER which had the green curve close to the shaded region, the green curve in the case of DEMO stays safely in the unshaded region. The blue curve is still in the unshaded region, but much closer to the boundary of the unshaded region than ITER (now ~1.8, much closer to 1 than in the case of ITER which was ~4). This shows an improvement for DEMO compared to ITER as it is closer to producing enough self-sustaining plasma current, though it will still need some help from other current-generating techniques which will be tested on ITER.
This function is part of release 2022.1 of the Fusion Energy Toolbox. Contact us at info@psatellite.com or call us at +01 609 275-9606 for more information.
