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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

DownScaleBench for developing and applying a deep learning based urban climate downscaling- first results for high-resolution urban precipitation climatology over Austin, Texas

Abstract Cities need climate information to develop resilient infrastructure and for adaptation decisions. The information desired is at the order of magnitudes finer scales relative to what is typically available from climate analysis and future projections. Urban downscaling refers to developing such climate information at the city (order of 1 – 10 km) and neighborhood (order of 0.1 – 1 km) resolutions from coarser climate products. Developing these higher resolution (finer grid spacing) data needed for assessments typically covering multiyear climatology of past data and future projections is complex and computationally expensive for traditional physics-based dynamical models. In this study, we develop and adopt a novel approach for urban downscaling by generating a general-purpose operator using deep learning. This ‘DownScaleBench’ tool can aid the process of downscaling to any location. The DownScaleBench has been generalized for both in situ (ground- based) and satellite or reanalysis gridded data. The algorithm employs an iterative super-resolution convolutional neural network (Iterative SRCNN) over the city. We apply this for the development of a high-resolution gridded precipitation product (300 m) from a relatively coarse (10 km) satellite-based product (JAXA GsMAP). The high-resolution gridded precipitation datasets is compared against insitu observations for past heavy rain events over Austin, Texas, and shows marked improvement relative to the coarser datasets relative to cubic interpolation as a baseline. The creation of this Downscaling Bench has implications for generating high-resolution gridded urban meteorological datasets and aiding the planning process for climate-ready cities.

Singh, Manmeet (ORCID:0000000233747149)↗
DOE OSTI2017

SNS Cryogenic Test Facility Kinney Vacuum Pump Commissioning and Operation at 2 K

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) has built and commissioned an independent Cryogenic Test Facility (CTF) in support of testing in the Radio-frequency Test Facility (RFTF). Superconducting Radio-frequency Cavity (SRF) testing was initially conducted with the CTF cold box at 4.5 K. A Kinney vacuum pump skid consisting of a roots blower with a liquid ring backing pump was recently added to the CTF system to provide testing capabilities at 2 K. System design, pump refurbishment and installation of the Kinney pump will be presented. During the commissioning and initial testing period with the Kinney pump, several barriers to achieve reliable operation were experienced. Details of these lessons learned and improvements to skid operations will be presented. Pump capacity data will also be presented.

Degraff, Brian D.↗
DOE OSTI2024

Peridynamic neural operators: A data-driven nonlocal constitutive model for complex material responses

Neural operators, which can act as implicit solution operators of hidden governing equations, have recently become popular tools for learning the responses of complex real-world physical systems. Nevertheless, most neural operator applications have thus far been data-driven and neglect the intrinsic preservation of fundamental physical laws in data. Here, in this work, we introduce a novel integral neural operator architecture called the Peridynamic Neural Operator (PNO) that learns a nonlocal constitutive law from data. This neural operator provides a forward model in the form of state-based peridynamics, with objectivity and momentum balance laws automatically guaranteed. As applications, we demonstrate the expressivity and efficacy of our model in learning complex material behaviors from both synthetic and experimental data sets. We also compare the performances with baseline models that use predefined constitutive laws. We show that, owing to its ability to capture complex responses, our learned neural operator achieves improved accuracy and efficiency. Moreover, by preserving the essential physical laws within the neural network architecture, the PNO is robust in treating noisy data. The method shows generalizability to different domain configurations, external loadings, and discretizations.

42 ENGINEERING↗
DOE OSTI2015

Spin-orbit torque induced spike-timing dependent plasticity

Nanoelectronic devices that mimic the functionality of synapses are a crucial requirement for performing cortical simulations of the brain. In this work, we propose a ferromagnet-heavy metal heterostructure that employs spin-orbit torque to implement spike-timing dependent plasticity. The proposed device offers the advantage of decoupled spike transmission and programming current paths, thereby leading to reliable operation during online learning. Possible arrangement of such devices in a crosspoint architecture can pave the way for ultra-dense neural networks. Simulation studies indicate that the device has the potential of achieving pico-Joule level energy consumption (maximum 2 pJ per synaptic event) which is comparable to the energy consumption for synaptic events in biological synapses.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

A domain wall-magnetic tunnel junction artificial synapse with notched geometry for accurate and efficient training of deep neural networks

Inspired by the parallelism and efficiency of the brain, several candidates for artificial synapse devices have been developed for neuromorphic computing, yet a nonlinear and asymmetric synaptic response curve precludes their use for backpropagation, the foundation of modern supervised learning. Spintronic devices—which benefit from high endurance, low power consumption, low latency, and CMOS compatibility—are a promising technology for memory, and domain-wall magnetic tunnel junction (DW-MTJ) devices have been shown to implement synaptic functions such as long-term potentiation and spike-timing dependent plasticity. In this work, we propose a notched DW-MTJ synapse as a candidate for supervised learning. Using micromagnetic simulations at room temperature, we show that notched synapses ensure the non-volatility of the synaptic weight and allow for highly linear, symmetric, and reproducible weight updates using either spin transfer torque (STT) or spin–orbit torque (SOT) mechanisms of DW propagation. We use lookup tables constructed from micromagnetics simulations to model the training of neural networks built with DW-MTJ synapses on both the MNIST and Fashion-MNIST image classification tasks. Accounting for thermal noise and realistic process variations, the DW-MTJ devices achieve classification accuracy close to ideal floating-point updates using both STT and SOT devices at room temperature and at 400 K. Our work establishes the basis for a magnetic artificial synapse that can eventually lead to hardware neural networks with fully spintronic matrix operations implementing machine learning.

42 ENGINEERING↗
DOE OSTI2022

Sustainability, Scalability, and Resiliency of the Town of Innisfil Mobility-on-Demand Experiment: Preliminary Results, Analyses, and Lessons Learned

In 2017, the town of Innisfil, Ontario, launched Innisfil Transit in partnership with Uber, a transportation network company, to provide a subsidized on-demand public mobility service as an alternative to investing in a new fixed-route bus service. The performance of Innisfil Transit is documented in a 2021 Ryerson University report by Sweet, Mitra, and Benaroya, which shows greater cost effectiveness of the mobility provided over the proposed bus alternative. This paper expands on those findings by assessing Innisfil Transit with respect to sustainability, scalability, and resiliency. First, we quantify the energy and emissions of this program relative to traditional transit and driving alone across varying powertrains. We then characterize a conservative first-order estimate of the percentage of US communities that fall within a similar spatial-demographic tier as Innisfil. Replicability also hinges on service cost and performance in comparison to average values for low-density transit in the US. Lastly, most transit agencies experienced a significant drop in demand (as much as 90%) with slowly rebounding ridership since the onset of the COVID-19 pandemic. The resiliency of the Innisfil program to the pressures induced by the pandemic is examined in comparison to other transit operations. The lessons learned across these three dimensions complement prior work to better understand the efficiency and sustainability of on-demand public mobility service for low-density communities like Innisfil.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗
DOE OSTI2022

Sustainability, Scalability and Resiliency of the Town of Innisfil Mobility-on-Demand Experiment: Preliminary Results, Analyses, and Lessons Learned: Preprint

In 2017, the Town of Innisfil, Ontario launched Innisfil Transit in partnership with Uber, a transportation network company, to provide a subsidized on-demand public mobility service as an alternative to investing in a new fixed-route bus service. The performance of Innisfil Transit is documented in a 2021 Ryerson University report which shows greater cost effectiveness of the mobility provided over the proposed bus alternative (Sweet, Mitra, and Benaroya 2021). This paper expands on those findings by assessing Innisfil Transit with respect to sustainability, scalability, and resiliency. First, we quantify the energy and emissions of this program relative to traditional transit and driving alone across varying powertrains. We then characterize a conservative first-order estimate of the percentage of US communities that fall within a similar spatial-demographic tier as Innisfil. Replicability also hinges on service cost and performance in comparison to average values for low-density transit in the US. Lastly, most transit agencies experienced a significant drop in demand (as much as 90%) with slowly rebounding ridership since the onset of the COVID-19 pandemic. The resiliency of the Innisfil program to the pressures induced by the pandemic is examined in comparison to other transit operations. The lessons learned across these three dimensions complement prior work to better understand the efficiency and sustainability of on-demand public mobility service for low-density communities like Innisfil.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

WE-G-213-01: Roentgen and the Birth of Modern Medical Physics

Roentgen and the Birth of Modern Medical Physics – Perry Sprawls Wilhelm Roentgen is well known for his discovery of x-radiation. What is less known and appreciated is his intensive research following the discovery to determine the characteristics of the “new kind of radiation” and demonstrate its great value for medical purposes. In this presentation we will imagine ourselves in Roentgen’s mind and follow his thinking, including questions and doubts, as he designs and conducts a series of innovative experiments that provided the foundation for the rapid growth of medical physics. Learning Objectives: Become familiar with the personal characteristics and work of Prof. Roentgen that establishes him as an inspiring model for the medical physics profession. Observe the thought process and experiments that determined and demonstrated the comprehensive characteristics of x-radiation. The AAPM Award Eponyms: William D. Coolidge, Edith H. Quimby, and Marvin M.D. Williams - Who were they and what did they do? – Lawrence N. Rothenberg William David Coolidge (1873–1975) William Coolidge was born in Hudson, NY in 1873. He obtained his BS at the Massacusetts Institute of Technology in 1896. Coolidge then went to the University of Leipzig, Germany for graduate study with physicists Paul Drude and Gustave Wiedemann and received a Ph.D. in 1899. While in Germany he met Wilhelm Roentgen. Coolidge returned to the US to teach at MIT where he was associated with Arthur A. Noyes of the Chemistry Department, working on the electrical conductivity of aqueous solutions. Willis R. Whitney, under whom Coolidge had worked before going to Germany, became head of the newly formed General Electric Research Laboratory and he invited Coolidge to work with him. In 1905, Coolidge joined the staff of the GE laboratory and was associated with it for the remainder of his life. He developed ductile tungsten filaments to replace fragile carbon filaments as the material for electric light bulb filaments. Until that innovation light bulbs had a notoriously short life. He later incorporated the ductile tungsten as a filament material for a hot cathode, fully evacuated x-ray tube, first described in 1912, which allowed higher current and x-ray output, and greater reliability than had previously been possible. These “Coolidge x-ray tubes” were far superior to the cold cathode, partial pressure gas x-ray tubes that had been in use since Roentgen’s discovery of x-rays in 1895. The Coolidge tube with incremental developments is now the key component for x-ray production in all of our modern x-ray imaging devices, such as CT scanners, interventional radiology systems, and mammography units. Coolidge was also involved in the development of sectional x-ray tubes for research and treatment that were initially designed to reach 800 kV. Additional improvements led to 1 MV and 2 MV devices. In 1932 Coolidge became director of the General Electric Research Laboratory, and in 1940, was made Vice-President and Director of Research. In 1945 he retired and was named Director Emeritus of the laboratory. Coolidge held 83 patents and was recognized for these and many other achievements by election to the National Academy of Engineers, a place in the Engineering Hall of Fame and the National Inventor’s Hall of Fame. The AAPM’s highest honor, the Coolidge Award, was named after him. He accepted Honorary Membership in the AAPM and was the first recipient of the AAPM Coolidge Award, which was presented to him in a special ceremony in Schenectady, NY in 1972 when he was 100 years old. Edith Hinckley Quimby (1891–1982) Edith Quimby was born in Rockford, IL in 1891. She graduated from Whitman College in Walla Walla, WA with a B.S. in 1913, and then obtained a masters degree from the University of California at Berkeley. Later in her career, after many significant achievements, Quimby was awarded honorary doctorates by Whitman College and Rutgers University. Edith Quimby was hired by Giacchino Failla as a radiation physicist at Memorial Hospital for Cancer in New York City. Failla had studied with Madame Curie and obtained his doctoral degree in her laboratory. After many groundbreaking medical physics studies from 1919 until 1942, they both moved to Columbia University. Dr. Quimby developed a widely employed dosimetry system for single plane implants with radium and radon seeds, and a dosimetry methodology for internal radionuclides. She was author of more than 75 scientific publications, and of significant textbooks including the first comprehensive physics textbook for radiologists “Physical Foundations of Radiology”, which was co-authored with Otto Glasser, Lauriston Taylor and James Weatherwax in the first edition, with Russell Morgan added for the second edition and Paul Goodwin for the fourth edition. With Sergei Feitelberg, M.D. she published two editions of “Radioactive Isotopes in Medicine and Biology: Basic Physics and Instrumentation”. Quimby became a renowned examiner for the American Board of Radiology when the third ABR examination, given in 1936, added physics. She served as President of the American Radium Society, received the RSNA Gold Medal, and also numerous prestigious awards given to women in science. Edith Quimby was a Charter Member of AAPM. The AAPM Lifetime Achievement Award was renamed the Edith H. Quimby Lifetime Achievement Award in her honor in 2011. Marvin Martin Dixon Williams (1902–1981) Marvin Williams was born in Walla Walla, WA in 1902, and attended the same college as Edith Quimby, graduating from Whitman College in 1926. He was greatly influenced to go into medical physics by her accomplishments. During his early career, Williams worked with James Weatherwax in Philadelphia while he was working toward an M.S. from the University of Pennsylvania. In 1931 Williams was awarded a Ph.D. in Biophysics from the University of Minnesota, with the work actually performed at the Mayo Clinic Graduate School of the University. While completing his Ph.D. studies, Marvin met Dr. Paul Hodges who had returned from the Peiping Union Medical College in Peiping (now Beijing), China. Hodges suggested that a physicist be sent to Peiping to install x-ray therapy equipment and a radon plant. Williams accepted the position and, in 1931, he and his wife Orpha left for China. Before going to China, Williams had spent time with the physics group at Memorial Hospital to learn about the operation of a radon plant. In China, he constructed the radon plant, employing 0.25 g of radium, and also installed the x-ray therapy unit. Williams and his wife returned to the US in 1935, and he accepted a research position at the Mayo Clinic. In 1950, he became Professor of Biophysics at Mayo, where he taught physics and biophysics until his retirement in 1967. Williams was also very active in the American Board of Radiology where, from 1944 through 1977, he examined over 3000 radiologists and 250 physicists. Marvin Williams was a Charter member of AAPM, served as the fourth President of AAPM in 1963, and was the fourth recipient the AAPM Coolidge Award in 1975. The Marvin Williams Award was originally established as the highest award of the American College of Medical Physics. When various functions of the ACMP were absorbed into the AAPM in 2012, the Marvin M D Williams Professional Achievement Award became one of the AAPM’s highest honors. Learning Objectives: Become familiar with the persons in whose honor the three major AAPM Award are named Learn about the achievements and activities which influenced the AAPM to name these awards in their honor.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-G-213-00: History Symposium: Radiological Physics Pioneers: Roentgen and the AAPM Award Eponyms - William Coolidge, Edith Quimby, and Marvin Williams - Who Were They and What Did They Do?

Roentgen and the Birth of Modern Medical Physics – Perry Sprawls Wilhelm Roentgen is well known for his discovery of x-radiation. What is less known and appreciated is his intensive research following the discovery to determine the characteristics of the “new kind of radiation” and demonstrate its great value for medical purposes. In this presentation we will imagine ourselves in Roentgen’s mind and follow his thinking, including questions and doubts, as he designs and conducts a series of innovative experiments that provided the foundation for the rapid growth of medical physics. Learning Objectives: Become familiar with the personal characteristics and work of Prof. Roentgen that establishes him as an inspiring model for the medical physics profession. Observe the thought process and experiments that determined and demonstrated the comprehensive characteristics of x-radiation. The AAPM Award Eponyms: William D. Coolidge, Edith H. Quimby, and Marvin M.D. Williams - Who were they and what did they do? – Lawrence N. Rothenberg William David Coolidge (1873–1975) William Coolidge was born in Hudson, NY in 1873. He obtained his BS at the Massacusetts Institute of Technology in 1896. Coolidge then went to the University of Leipzig, Germany for graduate study with physicists Paul Drude and Gustave Wiedemann and received a Ph.D. in 1899. While in Germany he met Wilhelm Roentgen. Coolidge returned to the US to teach at MIT where he was associated with Arthur A. Noyes of the Chemistry Department, working on the electrical conductivity of aqueous solutions. Willis R. Whitney, under whom Coolidge had worked before going to Germany, became head of the newly formed General Electric Research Laboratory and he invited Coolidge to work with him. In 1905, Coolidge joined the staff of the GE laboratory and was associated with it for the remainder of his life. He developed ductile tungsten filaments to replace fragile carbon filaments as the material for electric light bulb filaments. Until that innovation light bulbs had a notoriously short life. He later incorporated the ductile tungsten as a filament material for a hot cathode, fully evacuated x-ray tube, first described in 1912, which allowed higher current and x-ray output, and greater reliability than had previously been possible. These “Coolidge x-ray tubes” were far superior to the cold cathode, partial pressure gas x-ray tubes that had been in use since Roentgen’s discovery of x-rays in 1895. The Coolidge tube with incremental developments is now the key component for x-ray production in all of our modern x-ray imaging devices, such as CT scanners, interventional radiology systems, and mammography units. Coolidge was also involved in the development of sectional x-ray tubes for research and treatment that were initially designed to reach 800 kV. Additional improvements led to 1 MV and 2 MV devices. In 1932 Coolidge became director of the General Electric Research Laboratory, and in 1940, was made Vice-President and Director of Research. In 1945 he retired and was named Director Emeritus of the laboratory. Coolidge held 83 patents and was recognized for these and many other achievements by election to the National Academy of Engineers, a place in the Engineering Hall of Fame and the National Inventor’s Hall of Fame. The AAPM’s highest honor, the Coolidge Award, was named after him. He accepted Honorary Membership in the AAPM and was the first recipient of the AAPM Coolidge Award, which was presented to him in a special ceremony in Schenectady, NY in 1972 when he was 100 years old. Edith Hinckley Quimby (1891–1982) Edith Quimby was born in Rockford, IL in 1891. She graduated from Whitman College in Walla Walla, WA with a B.S. in 1913, and then obtained a masters degree from the University of California at Berkeley. Later in her career, after many significant achievements, Quimby was awarded honorary doctorates by Whitman College and Rutgers University. Edith Quimby was hired by Giacchino Failla as a radiation physicist at Memorial Hospital for Cancer in New York City. Failla had studied with Madame Curie and obtained his doctoral degree in her laboratory. After many groundbreaking medical physics studies from 1919 until 1942, they both moved to Columbia University. Dr. Quimby developed a widely employed dosimetry system for single plane implants with radium and radon seeds, and a dosimetry methodology for internal radionuclides. She was author of more than 75 scientific publications, and of significant textbooks including the first comprehensive physics textbook for radiologists “Physical Foundations of Radiology”, which was co-authored with Otto Glasser, Lauriston Taylor and James Weatherwax in the first edition, with Russell Morgan added for the second edition and Paul Goodwin for the fourth edition. With Sergei Feitelberg, M.D. she published two editions of “Radioactive Isotopes in Medicine and Biology: Basic Physics and Instrumentation”. Quimby became a renowned examiner for the American Board of Radiology when the third ABR examination, given in 1936, added physics. She served as President of the American Radium Society, received the RSNA Gold Medal, and also numerous prestigious awards given to women in science. Edith Quimby was a Charter Member of AAPM. The AAPM Lifetime Achievement Award was renamed the Edith H. Quimby Lifetime Achievement Award in her honor in 2011. Marvin Martin Dixon Williams (1902–1981) Marvin Williams was born in Walla Walla, WA in 1902, and attended the same college as Edith Quimby, graduating from Whitman College in 1926. He was greatly influenced to go into medical physics by her accomplishments. During his early career, Williams worked with James Weatherwax in Philadelphia while he was working toward an M.S. from the University of Pennsylvania. In 1931 Williams was awarded a Ph.D. in Biophysics from the University of Minnesota, with the work actually performed at the Mayo Clinic Graduate School of the University. While completing his Ph.D. studies, Marvin met Dr. Paul Hodges who had returned from the Peiping Union Medical College in Peiping (now Beijing), China. Hodges suggested that a physicist be sent to Peiping to install x-ray therapy equipment and a radon plant. Williams accepted the position and, in 1931, he and his wife Orpha left for China. Before going to China, Williams had spent time with the physics group at Memorial Hospital to learn about the operation of a radon plant. In China, he constructed the radon plant, employing 0.25 g of radium, and also installed the x-ray therapy unit. Williams and his wife returned to the US in 1935, and he accepted a research position at the Mayo Clinic. In 1950, he became Professor of Biophysics at Mayo, where he taught physics and biophysics until his retirement in 1967. Williams was also very active in the American Board of Radiology where, from 1944 through 1977, he examined over 3000 radiologists and 250 physicists. Marvin Williams was a Charter member of AAPM, served as the fourth President of AAPM in 1963, and was the fourth recipient the AAPM Coolidge Award in 1975. The Marvin Williams Award was originally established as the highest award of the American College of Medical Physics. When various functions of the ACMP were absorbed into the AAPM in 2012, the Marvin M D Williams Professional Achievement Award became one of the AAPM’s highest honors. Learning Objectives: Become familiar with the persons in whose honor the three major AAPM Award are named Learn about the achievements and activities which influenced the AAPM to name these awards in their honor.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-G-213-02: The AAPM Award Eponyms: William D. Coolidge, Edith H. Quimby, and Marvin M.D. Williams - Who Were They and What Did They Do?

Roentgen and the Birth of Modern Medical Physics – Perry Sprawls Wilhelm Roentgen is well known for his discovery of x-radiation. What is less known and appreciated is his intensive research following the discovery to determine the characteristics of the “new kind of radiation” and demonstrate its great value for medical purposes. In this presentation we will imagine ourselves in Roentgen’s mind and follow his thinking, including questions and doubts, as he designs and conducts a series of innovative experiments that provided the foundation for the rapid growth of medical physics. Learning Objectives: Become familiar with the personal characteristics and work of Prof. Roentgen that establishes him as an inspiring model for the medical physics profession. Observe the thought process and experiments that determined and demonstrated the comprehensive characteristics of x-radiation. The AAPM Award Eponyms: William D. Coolidge, Edith H. Quimby, and Marvin M.D. Williams - Who were they and what did they do? – Lawrence N. Rothenberg William David Coolidge (1873–1975) William Coolidge was born in Hudson, NY in 1873. He obtained his BS at the Massacusetts Institute of Technology in 1896. Coolidge then went to the University of Leipzig, Germany for graduate study with physicists Paul Drude and Gustave Wiedemann and received a Ph.D. in 1899. While in Germany he met Wilhelm Roentgen. Coolidge returned to the US to teach at MIT where he was associated with Arthur A. Noyes of the Chemistry Department, working on the electrical conductivity of aqueous solutions. Willis R. Whitney, under whom Coolidge had worked before going to Germany, became head of the newly formed General Electric Research Laboratory and he invited Coolidge to work with him. In 1905, Coolidge joined the staff of the GE laboratory and was associated with it for the remainder of his life. He developed ductile tungsten filaments to replace fragile carbon filaments as the material for electric light bulb filaments. Until that innovation light bulbs had a notoriously short life. He later incorporated the ductile tungsten as a filament material for a hot cathode, fully evacuated x-ray tube, first described in 1912, which allowed higher current and x-ray output, and greater reliability than had previously been possible. These “Coolidge x-ray tubes” were far superior to the cold cathode, partial pressure gas x-ray tubes that had been in use since Roentgen’s discovery of x-rays in 1895. The Coolidge tube with incremental developments is now the key component for x-ray production in all of our modern x-ray imaging devices, such as CT scanners, interventional radiology systems, and mammography units. Coolidge was also involved in the development of sectional x-ray tubes for research and treatment that were initially designed to reach 800 kV. Additional improvements led to 1 MV and 2 MV devices. In 1932 Coolidge became director of the General Electric Research Laboratory, and in 1940, was made Vice-President and Director of Research. In 1945 he retired and was named Director Emeritus of the laboratory. Coolidge held 83 patents and was recognized for these and many other achievements by election to the National Academy of Engineers, a place in the Engineering Hall of Fame and the National Inventor’s Hall of Fame. The AAPM’s highest honor, the Coolidge Award, was named after him. He accepted Honorary Membership in the AAPM and was the first recipient of the AAPM Coolidge Award, which was presented to him in a special ceremony in Schenectady, NY in 1972 when he was 100 years old. Edith Hinckley Quimby (1891–1982) Edith Quimby was born in Rockford, IL in 1891. She graduated from Whitman College in Walla Walla, WA with a B.S. in 1913, and then obtained a masters degree from the University of California at Berkeley. Later in her career, after many significant achievements, Quimby was awarded honorary doctorates by Whitman College and Rutgers University. Edith Quimby was hired by Giacchino Failla as a radiation physicist at Memorial Hospital for Cancer in New York City. Failla had studied with Madame Curie and obtained his doctoral degree in her laboratory. After many groundbreaking medical physics studies from 1919 until 1942, they both moved to Columbia University. Dr. Quimby developed a widely employed dosimetry system for single plane implants with radium and radon seeds, and a dosimetry methodology for internal radionuclides. She was author of more than 75 scientific publications, and of significant textbooks including the first comprehensive physics textbook for radiologists “Physical Foundations of Radiology”, which was co-authored with Otto Glasser, Lauriston Taylor and James Weatherwax in the first edition, with Russell Morgan added for the second edition and Paul Goodwin for the fourth edition. With Sergei Feitelberg, M.D. she published two editions of “Radioactive Isotopes in Medicine and Biology: Basic Physics and Instrumentation”. Quimby became a renowned examiner for the American Board of Radiology when the third ABR examination, given in 1936, added physics. She served as President of the American Radium Society, received the RSNA Gold Medal, and also numerous prestigious awards given to women in science. Edith Quimby was a Charter Member of AAPM. The AAPM Lifetime Achievement Award was renamed the Edith H. Quimby Lifetime Achievement Award in her honor in 2011. Marvin Martin Dixon Williams (1902–1981) Marvin Williams was born in Walla Walla, WA in 1902, and attended the same college as Edith Quimby, graduating from Whitman College in 1926. He was greatly influenced to go into medical physics by her accomplishments. During his early career, Williams worked with James Weatherwax in Philadelphia while he was working toward an M.S. from the University of Pennsylvania. In 1931 Williams was awarded a Ph.D. in Biophysics from the University of Minnesota, with the work actually performed at the Mayo Clinic Graduate School of the University. While completing his Ph.D. studies, Marvin met Dr. Paul Hodges who had returned from the Peiping Union Medical College in Peiping (now Beijing), China. Hodges suggested that a physicist be sent to Peiping to install x-ray therapy equipment and a radon plant. Williams accepted the position and, in 1931, he and his wife Orpha left for China. Before going to China, Williams had spent time with the physics group at Memorial Hospital to learn about the operation of a radon plant. In China, he constructed the radon plant, employing 0.25 g of radium, and also installed the x-ray therapy unit. Williams and his wife returned to the US in 1935, and he accepted a research position at the Mayo Clinic. In 1950, he became Professor of Biophysics at Mayo, where he taught physics and biophysics until his retirement in 1967. Williams was also very active in the American Board of Radiology where, from 1944 through 1977, he examined over 3000 radiologists and 250 physicists. Marvin Williams was a Charter member of AAPM, served as the fourth President of AAPM in 1963, and was the fourth recipient the AAPM Coolidge Award in 1975. The Marvin Williams Award was originally established as the highest award of the American College of Medical Physics. When various functions of the ACMP were absorbed into the AAPM in 2012, the Marvin M D Williams Professional Achievement Award became one of the AAPM’s highest honors. Learning Objectives: Become familiar with the persons in whose honor the three major AAPM Award are named Learn about the achievements and activities which influenced the AAPM to name these awards in their honor.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Operator inference for non-intrusive model reduction of systems with non-polynomial nonlinear terms

Here in this work we present a non-intrusive model reduction method to learn low-dimensional models of dynamical systems with non-polynomial nonlinear terms that are spatially local and that are given in analytic form. In contrast to state-of-the-art model reduction methods that are intrusive and thus require full knowledge of the governing equations and the operators of a full model of the discretized dynamical system, the proposed approach requires only the non-polynomial terms in analytic form and learns the rest of the dynamics from snapshots computed with a potentially black-box full-model solver. The proposed method learns operators for the linear and polynomially nonlinear dynamics via a least-squares problem, where the given non-polynomial terms are incorporated on the right-hand side. The least-squares problem is linear and thus can be solved efficiently in practice. The proposed method is demonstrated on three problems governed by partial differential equations, namely the diffusion–reaction Chafee–Infante model, a tubular reactor model for reactive flows, and a batch-chromatography model that describes a chemical separation process. The numerical results provide evidence that the proposed approach learns reduced models that achieve comparable accuracy as models constructed with state-of-the-art intrusive model reduction methods that require full knowledge of the governing equations.

42 ENGINEERING↗
DOE OSTI2026

Structure-aware Initialization via Numerical Continuation and Informed Priors

Scientific machine learning (SciML) often operates in ill-conditioned, weakly identifiable regimes due to limited data or indirect observations. In such settings, optimization and inference are highly sensitive to the starting point, making initialization--often under-reported--a consequential degree of freedom. Random initialization is not a neutral default as it induces an implicit prior over candidate solutions and can systematically bias the result, producing large run-to-run variability. Here, we formalize this view by treating initialization as a hidden confounder in SciML and develop a unifying theory for structure-aware initialization via numerical continuation, constructing warm starts from related problem instances. Across representative tasks, including physics-informed neural networks, maximum likelihood estimation, and variational inference, warm starts have been shown to consistently reduce optimization effort and improve reliability.

Data integrity↗
DOE OSTI2022

Monitoring Operational States of a Nuclear Reactor Using Seismoacoustic Signatures and Machine Learning

Monitoring nuclear reactors is an important safety and security task with growing requirements. We explore the possibility of using seismic and acoustic data for inferring the power level of an operating reactor. Continuous data recorded at a single seismoacoustic station that is located about 50 m away from a research reactor was visualized and analyzed. The data show a clear correlation between seismoacoustic features and reactor main operational states. We designed a workflow that includes two machine learning (ML) models to classify the reactor operational states (OFF, transition, and ON) and estimate reactor power levels (10%, 30%, 50%, 70%, and 90%). We applied and compared five ML algorithms for the reactor OFF-transition-ON and four approaches for the power level classification. We also compared the performance of ML models trained with seismic-only, acoustic-only, and both types of data. Five-fold cross validations were implemented to assure a thorough evaluation of the model performances. Additionally, the results show the extreme boosting gradient algorithm worked best for the first model, whereas random forests performed best for the second model. Combining seismic and acoustic data leads to better performance than using a single type of data. Seismic data contributed more than acoustic data for both models. We reached an accuracy of 0.98 for reactor OFF and ON. The accuracies for the transition state and power levels are less optimal with a minimum accuracy of 0.66. However, our results suggest seismic and acoustic data contain useful information about the transition state as well as power levels. Seismic and acoustic data could be integrated with other observations to improve monitoring performance.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Pansharpening via coupled triple factorization dictionary learning

Data fusion is the operation of integrating data from different modalities to construct a single consistent representation. Here, this paper proposes variations of coupled dictionary learning through an additional factorization. One variation of this model is applicable to the pansharpening data fusion problem. Real world pansharpening data was applied to train and test our proposed formulation. The results demonstrate that the data fusion model can successfully be applied to the pan-sharpening problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

SU-F-P-08: Medical Physics Perspective On Radiation Therapy Quality and Safety Considerations in Low Income Settings

Purpose: The last few years have seen a significant growth of interest in the global radiation therapy crisis. Various organizations are quantifying the need and providing aid in support of addressing the shortfall existing in many low-to-middle income countries (LMICs). The Lancet Oncology Commission report (Lancet Oncol. Sep;16(10):1153-86, 2015) projects a need of 22,000 new medical physicists in LMICs by 2035 if there is to be equal access globally. With the tremendous demand for new facilities, equipment and personnel, it is very important to recognize quality and safety considerations and to address them directly. Methods: A detailed examination of quality and safety publications was undertaken. A paper by Dunscombe (Front. Oncol. 2: 129, 2012) reviewed the recommendations of 7 authoritative reports on safety in radiation therapy and found the 12 most cited recommendations, summarized in order of most to least cited: training, staffing, documentation/standard operating procedures, incident learning, communication/questioning, check lists, QC/PM, dosimetric audit, accreditation, minimizing interruptions, prospective risk assessment, and safety culture. However, these authoritative reports were generally based on input from high income contexts. In this work, the recommendations were analyzed with a special emphasis on issues that are significant in LMICs. Results: The review indicated that there are significant challenges in LMICs with training and staffing ranking at the top in terms quality and safety. Conclusion: With the recognized need for expanding global access to radiation therapy, especially in LMICs, and the backing by multiple support organizations, quality and safety considerations must be overtly addressed. While multidimensional, training and staffing are top priorities. The use of outdated systems with poor interconnectivity, coupled with a lack of systematic QA in high patient load settings are additional concerns. Any support provided to lower resourced settings must address the multiple facets associated with these quality and safety indicators.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Quantum biology revisited

Photosynthesis is a highly optimized process from which valuable lessons can be learned about the operating principles in nature. Its primary steps involve energy transport operating near theoretical quantum limits in efficiency. Recently, extensive research was motivated by the hypothesis that nature used quantum coherences to direct energy transfer. This body of work, a cornerstone for the field of quantum biology, rests on the interpretation of small-amplitude oscillations in two-dimensional electronic spectra of photosynthetic complexes. This Review discusses recent work reexamining these claims and demonstrates that interexciton coherences are too short lived to have any functional significance in photosynthetic energy transfer. Instead, the observed long-lived coherences originate from impulsively excited vibrations, generally observed in femtosecond spectroscopy. These efforts, collectively, lead to a more detailed understanding of the quantum aspects of dissipation. Nature, rather than trying to avoid dissipation, exploits it via engineering of exciton-bath interaction to create efficient energy flow.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Cryogenic control system operational experience at SNS

Abstract The helium cryogenic system at Spallation Neutron Source (SNS) provides cooling to 81 superconducting radio frequency cavities. To support the operation of the cryogenic facility, a highly reliable control system consisting of software, hardware, and Human Machine Interface (HMI) has been developed and improved during the first fifteen years of operation. Integrating the cryogenic control system with other subsystems of the SNS complex is an important aspect to the success of the operation. The operating experience, lessons learned and recommendations to consider for future facilities will be detailed in this paper.

Howell, M. (ORCID:0000000310360707)↗