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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Mapping potentials and bridging regional gaps of renewable resources in China

Reasonable and effective use of renewable resources can reduce dependence on traditional fossil-based energy sources and reduce carbon emissions. This study mapped the spatial potentials of renewable resources (i.e., solar radiation, precipitation, wind, and geothermal resources) in China. The results showed that China's most abundant renewable resources are located in the southwestern regions, which are significantly different from the spatial distribution patterns of population and economic development. Four southwestern provinces (Tibet, Qinghai, Sichuan, and Yunnan) make up only 7% of the national gross domestic product (GDP) and 30% of the national land area but possess 58% of the renewable resources. Furthermore, we found a weak to moderate degree of negative correlation between the emergy density of renewable resources and GDP per capita on the administrative levels of the prefecture-level cities for the whole country and in its eastern, central, and western regions. This means that the socioeconomically underdeveloped Midwest has more abundant renewable resources. A distributed energy-economic system may help to bridge the regional gaps of renewable sources in China. These findings can support policy decisions for the better development and use of renewable resources in China.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Virtual to Physical: Reinforcement Learning to Optimize SNS Particle Accelerator Controls

Complex accelerators must have control systems that can handle dynamic nonlinear environments. This makes traditional control methods unsuitable as they can struggle to adapt to these uncertainties. This provides an ideal environment for reinforcement learning algorithms as they are adaptable and generalizable. We present a reinforcement learning pipeline that can effectively handle the dynamics of a complex accelerator. We test and prove our pipelines capabilities on multiple environments including the Spallation Neutron Source (SNS) and the Beam Test Facility (BTF) at Oakridge National Lab (ORNL). Due to the limited time available to train an online algorithm like reinforcement learning on a real accelerator, we utilize a virtual twin accelerator (VIRAC) developed by ORNL to pretrain the policy and show its ability to converge in the virtual environment. We then test the adaptability of the pretrained RL model by applying it on the real accelerator and comparing the results. Utilizing our Scientific Optimization and Controls Toolkit (SOCT) and open-source standards such as Gymnasium we create and solve for a MEBT orbit correction problem in the SNS and an emittance maximization problem in the BTF. We show how Twin Delayed Deep Deterministic Policy Gradient (TD3) can solve this optimization environment in the virtual accelerator and transfer this policy onto the real accelerator for inference and model retraining. We show how reinforcement learning can be utilized as a control system for complex accelerators and provide a model pipeline for how an implementation performs and can be adapted to new accelerator control problems.

Kasparian, Armen [Thomas Jefferson National Accele↗
DOE OSTI2026

Using Flory–Huggins-informed human-in-the-loop Bayesian optimization to map the phase diagram of polymer blends

Mapping the phase diagram of polymer blends is an essential step in controlling the structure–property relationship of polymer-based materials. However, traditional grid-based approaches are inefficient and rely on subjective judgements for terminating the experimental campaign. Artificial intelligence-guided experimentation offers a compelling alternative, especially when data-driven decision-making is interfaced with established polymer thermodynamics to improve efficiency and interpretability. Here, we introduce a physics-informed Bayesian optimization approach to guide the mapping of the phase diagram of a model blend containing poly(methyl methacrylate) and poly(styrene-ran-acrylonitrile). Physical information is derived from a Flory–Huggins representation of the spinodal curve, which is integrated into the Bayesian optimization process as a structured prior mean that acts as a soft constraint. Implemented as a human-in-the-loop workflow, the approach leverages optical imaging of film cloudiness with iterative Gaussian process surrogate modeling and a parameter selection decision policy to identify the composition-temperature conditions for sequential iterations. Convergence of kernel and Flory–Huggins-based hyperparameters provided a stopping criterion, ensuring an objective and interpretable termination of the experimental campaign. The framework recovered the known lower critical solution temperature (∼160 °C), while increasing material efficiency through targeted sampling. This work establishes a proof-of-concept for the application of Bayesian optimization workflows to study polymer blend miscibility.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Optimal Control of SOEC-Based Hydrogen Production Systems for Demand Response Using Deep Reinforcement Learning in Smart Grids

Solid oxide electrolysis cell (SOEC) hydrogen production technology can range in size from small, appliance-size equipment to large-scale, central production facilities that can be tied directly to renewable or non-greenhouse-gas-emitting forms of electricity production, making it an ideal resource for demand response (DR). The SOEC hydrogen production system is a complex integrated system that encompasses fluid dynamics, electrical dynamics, and electrochemical and thermal dynamics, all of which involve non-linearity and non-convexity. Proper control of the SOEC hydrogen production system is crucial to enable its participation in the DR program. Here, to overcome the difficulty of designing an explicit control law for such nonlinear systems with nonconvex optimization features in DR applications, deep reinforcement learning (DRL) is explored to achieve the optimal control of the SOEC system for DR participation. Specifically, a twin delayed deterministic policy gradient (TD3) control framework is applied to achieve optimal response performance during DR events by considering power tracking error and hydrogen production efficiency with a suitable reward function. Two case studies with grid connections for tracking different DR commands were investigated. The first case study involved operating conditions reaching the boundaries, while the second involved operating conditions within the boundaries. The results showed that the proposed DRL-based control for SOEC can track the DR signal in a timely manner while maintaining high energy efficiency.

08 HYDROGEN↗
DOE OSTI2026

Aligning NASA Earth Science Data Stewardship with FAIR Principles: Outcomes, Recommendations, and Future Directions

The FAIR Principles—Findable, Accessible, Interoperable, and Reusable—offer a widely accepted framework for improving the sharing and reuse of digital scientific data by both human and machine users. Following these principles is critical for effective scientific data stewardship, broader scientific collaboration, and compliance with federal and agency data policies. This paper, based on the work of NASA’s Open, Free, and FAIR Working Group (O’FAIR WG) under the Earth Science Data Systems Program, presents an overview of how FAIR is being applied within NASA’s Earth science data landscape. It highlights ongoing progress and challenges, identifies FAIR-enabling resources, and offers recommendations and strategic actions to enhance the FAIRness of NASA-funded open and free Earth science data products. The FAIR-enabling resources identified underscore the vital role of NASA's existing enterprise processes, standards, tools, and infrastructures in supporting FAIR implementation. Our findings show strong performance in making NASA Earth science data more findable and accessible. However, further work is needed—especially in enhancing interoperability, so that different systems and tools can better understand and exchange data. This is especially important for enabling machine-driven discovery and analysis. We emphasize the importance of a balanced strategy that combines a centralized, top-down approach—focused on building enterprise-level capabilities and processes—with a decentralized, bottom-up approach driven by discipline-specific needs and community practices. We advocate for coordinated efforts to enhance (meta)data interoperability to facilitate seamless data and information sharing and exchange of Earth science data both within NASA and across other agencies managing Earth science data.

Data Product↗
NASA NTRS1980

Modal cost analysis for linear matrix-second-order systems

Reduced models and reduced controllers for systems governed by matrix-second-order differential equations are obtained by retaining those modes which make the largest contributions to quadratic control objectives. Such contributions, expressed in terms of modal data, used as mode truncation criteria, allow the statement of the specific control objectives to influence the early model reduction from very high order models which are available, for example, from finite element methods. The relative importance of damping, frequency, and eigenvector in the mode truncation decisions are made explicit for each of these control objectives: attitude control, vibration suppression and figure control. The paper also shows that using modal cost analysis (MCA) on the closed loop modes of the optimally controlled system allows the construction of reduced control policies which feedback only those closed loop modal coordinates which are most critical to the quadratic control performance criterion. In this way, the modes which should be controlled (and hence the modes which must be observable by choice of measurements), are deduced from truncations of the optimal controller.

Skelton, R. E.↗
DOE OSTI2019

Concepts for Autonomous Operation of Microreactors

Microreactor concepts have seen increasing interest in recent years given their potential use for meeting energy needs in remote and grid-isolated communities. Given the small power outputs of microreactors and the potential for remote siting, there is a need to reduce operational staffing levels to improve their economic viability. A key enabling technology for this purpose is autonomous control that enables autonomous operation of microreactors. While several options for autonomous control exist, the level of human operator involvement in operational decision making needs to be defined as part of the system design process. Once this separation of function is achieved, several options exist for autonomous control ranging from simple automation of some procedures to fully autonomous operational mode decision making and execution.A critical aspect of autonomous decision making is the ability to have as complete an awareness of the system state as possible. In addition to data on temperature, pressure, flow, and neutron flux, measurements of the condition of important components will be necessary. This type of information will allow the autonomous control system to adapt its decision making to any changing conditions within the reactor, thereby not compromising safety while continuing to operate for as long as possible. Several technical advances are needed before widespread use of autonomous control in microreactors. These include sensor and instrumentation technologies that are capable of long term, unattended operation in harsh environments, technologies for inferring the state of the microreactor system or subsystems in an automated fashion, algorithms for predictive decision making that account for the assessed condition of the microreactor subsystems as well as the potential impact on those components of any operational decision, and actuators and control system hardware that are also long-lived in a harsh environment. In addition, given the need to remotely monitor the operations, cybersecurity requirements will likely need to be imposed to ensure secure operations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Getting Innovation Right

As we celebrate the fiftieth anniversary of the Apollo 11 moon landing, the importance of science and technology advancement and innovation is front and center. The role of innovation is easily recognized—it changes, improves and, in many cases, replaces and makes obsolete the tools used in our daily lives. Innovation is shaped by the mission, degree of competition, and urgency to find a “solution.” Notably, often it is no longer shaped by the strategies of a few governments. The commercial and global aspects of the private sector have vastly complicated the ability to direct innovation towards good public purpose and not only for individual gain.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

California Energy Systems for the 21st Century (CES-21) Program, CRADA TC02200 (Final Report)

The following report representsthe culmination of a five-year Cybersecurity Research and Development (R&D) program performed by California’s Investor-Owned Utilities (IOUs) and Lawrence Livermore National Laboratory (LLNL) and funded by the IOUs’ electricity ratepayers as authorized by California Legislation and the California Public Utilities Commission (CPUC). The cybersecurity R&D, which was intensely technical in nature, was broken into three major workstreams: 1. The development of a modeling & simulation platform, to explore the potential effects of various threat and response scenarios at grid scale; 2. The establishment of a physical testbed with separate substation instances from each of the IOUs, to evaluate threats and responses on actual substation equipment; 3. The development of a research package consisting of several capabilities to support the industry’s evolution towards automated threat response and other next-generation cybersecurity techniques Throughout the program, there was extensive collaboration between the program team and national laboratories, federal departments, academic institutions and industry organizations. Several of the tools developed through the program have been made available to the open source community, to enable faster adoption and continued development of important cybersecurity capabilities. While this program began to develop much of the foundation for automated threat response, much work remains to be done, and this report recommends a series of next steps. While the Executive Summary below has been simplified as much as possible, the very technical nature of the subject matter would make further reduction difficult without causing meaning to be lost. Due to the sensitive nature of the research, some topics are intentionally covered at a high level to protect the research and therefore the electric grid and customers of California and the Nation. For further detail, clarification or questions we suggest discussion with the program team.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Supporting ARPA-E Power Grid Optimization (Final Report)

Pacific Northwest National Laboratory (PNNL), Arizona State University (ASU), Georgia Institute of Technology (Georgia Tech), Los Alamos National Laboratory (LANL), National Renewable Energy Laboratory (NREL), Texas A&M University (TAMU), The University of Texas at Austin (UT), and the University of Wisconsin-Madison (UW-M) supported the ARPA-E Grid Optimization (GO) Competition by providing a common problem formulation, data format, datasets, evaluation mechanism, scoring, rules, and results that resulted in the awarding of $\$9.24$ million dollars to teams from academia, industry, and national labs for solving three sets of increasingly difficult non-linear, security- constrained AC Optimal Powerflow (AC-OPF) optimization problems in order to increase the efficiency of the US Electric Grid. It is estimated that a 1% increase in efficiency can save $\$1$ billion. Current industry practices typically use a linear DC model (DC-OPF) in order solve the OPF problem within the time constraints of the operation schedule. The GO Competition challenges the best power engineers, mathematicians, and computer scientists to make possible operational decisions based on accurate physical models. To accomplish this, the GO Competition created a series of Challenges and funded teams to produce the best solver. Challenge 1 was to solve the security constrained Alternating Current Optimal Power Flow (ACOPF) problem. Challenge 2 extended that to by adding adjustable transformer tap ratios, phase shifting transformers, switchable shunts, price-responsive demand, ramp rate constrained generators and loads, and fast-start unit commitment (UC). Furthermore, Challenge 2 was a maximization problem while Challenge 1 was a minimization problem. While Challenge 3 was being developed, the entrants were invited to find better solutions to the Challenge 2 synthetic datasets with no restrictions on time, hardware, or algorithms. The Challenge 2 solutions turned out to be very good. Challenge 3 expanded the Challenge 2 problem further by using multiperiod dynamic markets, including advisory models for extreme weather events, day-ahead markets, and the real-time markets with an extended look-ahead. These problems included active bid-in demand and topology optimization. Together the Challenges used nearly 30 million CPU hours. Since each team was working on the same problem, using the same data, and running on the same hardware, fair comparisons could be drawn as to the best solver. The datasets were varied enough, however, that the best solver for one dataset was not necessarily the best at another, so cumulative scores were used. The process was managed by the PNNL maintained website https://GOCompetition.energy.gov, where Entrants could find information about the problem, the data, the rules, submit their solver for evaluation, and see the scores of all the competing teams on a Leaderboard. Interest was world-wide but only American teams were eligible for prizes. The Competition has produced 34 journal articles 115 papers and been cited over 500 times in the literature, including 12 dissertations (4 from foreign countries; Columbia (2), Germany, and Italy) and 3 from the DOE ExaScale project. Software developed by Pearl Street Technologies for Challenges 1 and 2 is now deployed by Southwest Power Pool (SPP) and Midcontinent Independent Service Operator (MISO). Other teams have received inquiries from venture capitalists. Google DeepMind has thanked the Competition for making the datasets developed for the Competition public. They are using it to train machine learning models. The larger datasets have billions of unknowns to be solved for, but only a small percent matter in the final solution. Knowing what unknowns are important can dramatically speedup the solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Introduction to the Bioproduct Transition Dynamics Model

The U.S. Department of Energy, Bioenergy Technologies Office has a broad understanding of different conversion processes that produce bioproducts (chemicals derived from biomass feedstocks) and the market attributes of those processes. However, bioproducts have in many cases proven to be difficult to scale up to commercial production and bring to market, and there is currently a need for greater understanding around the possible successful scenarios for advancing the bioproducts industry. Insight into the myriad factors that impact the success of individual bioproducts and the growth of the bioproducts industry will enable bioproduct stakeholders to evaluate strategies for development and investment that could achieve the greatest impact. An understanding of these factors will also enable the identification of synergies between the bioproducts and biofuels industries that occur through shared learning and co-production. The Bioproduct Transition Dynamics (BTD) model explores questions such as the following: what are the factors that separate a successful, commercially produced bioproduct like succinic acid from one that never progresses beyond bench-scale lab research? Can these factors be influenced by stakeholders, and to what extent? The BTD model uses system dynamics to capture the impacts of investor decision-making, bioproduct techno-economics, and market factors during the early stages of bioproduct development. Key components of the BTD model include techno-economic benchmarks that inform the investor decision-making process, failures and setbacks in development and the resulting need for additional work, and the impacts of effective or ineffective management during each development stage. These factors and their interactions are tracked through bench-scale laboratory research, piloting, demoing, and the construction and operation of the first commercial-scale plant. Bioproduct development is linked to the biofuels industry through a shared-learning model, enabling the benefit to biofuels from bioproduct technology and feedstock supply chain development to be quantified. A wide variety of bioproducts can be analyzed using the BTD model, including bioproducts that have been developed through economic or policy-driven mechanisms, and those with either niche (low volume) or scalable (high volume) markets. The BTD model also has the potential to apply to technology development processes outside the bioproducts industry; background research performed for this project has shown that the early stages of technology development are similar, and impacted by similar factors, regardless of the exact industry. This presentation will cover the BTD model logic, input data, validation process, and results of a sensitivity analysis based on techno-economic data for succinic acid. The sensitivity analysis was performed to identify factors with the largest impact on the eventual success or failure of a bioproduct. Results indicate that management effectiveness, which affects how efficiently money spent is converted into technological advancements, is the single most important factor in determining whether a bioproduct reaches commercial-scale production. The capacity of the first commercial plant and the type of biomass feedstock used, as well as the presence of government support in the form of cost-sharing, were also identified as significant factors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

A System Dynamics Model of Early-Stage Transition Dynamics in the Bioproducts Industry

The U.S. Department of Energy, Bioenergy Technologies Office has a broad understanding of different conversion processes that produce bioproducts (chemicals derived from biomass feedstocks) and the techno-economic attributes of those processes. However, bioproducts have in many cases proven to be difficult to scale up to commercial production, and there is currently a need for greater understanding around the possible successful scenarios for advancing the bioproducts industry. Insight into the myriad factors that impact the success of individual bioproducts and the growth of the bioproducts industry will enable bioproduct stakeholders to evaluate strategies for development and investment that could achieve the greatest impact. An understanding of these factors will also enable the identification of synergies between the bioproducts and biofuels industries that occur through shared learning and co-production. The Bioproduct Transition Dynamics (BTD) model explores questions such as the following: what are the factors that separate a successful, commercially produced bioproduct like succinic acid from one that never progresses beyond bench-scale lab research? Can these factors be influenced by stakeholders, and to what extent? The BTD model uses system dynamics to capture the impacts of investor decision-making, bioproduct techno-economics, and end use factors during the early stages of bioproduct development. Key components of the BTD model include techno-economic benchmarks that inform the investor decision-making process, failures and setbacks in development and the resulting need for additional work, and the impacts of effective or ineffective management during each development stage. These factors and their interactions are tracked through bench-scale laboratory research, piloting, demoing, and the construction and operation of the first commercial-scale plant. Bioproduct development is linked to the biofuels industry through a shared-learning model, enabling the benefit to biofuels from bioproduct technology and feedstock supply chain development to be quantified. A wide variety of bioproducts can be analyzed using the BTD model, including bioproducts that have been developed through economic or policy-driven mechanisms, and those with either niche (low volume) or scalable (high volume) demand. The BTD model also has the potential to apply to technology development processes outside the bioproducts industry; background research performed for this project has shown that the early stages of technology development are similar, and impacted by similar factors, regardless of the exact industry. This presentation will cover the BTD model logic, input data, validation process, and results of a sensitivity analysis based on techno-economic data for succinic acid. The sensitivity analysis was performed to identify factors with the largest impact on the eventual success or failure of a bioproduct. Results indicate that management effectiveness, which affects how efficiently money spent is converted into technological advancements, is the single most important factor in determining whether a bioproduct reaches commercial-scale production. The capacity of the first commercial plant and the type of biomass feedstock used, as well as the presence of government support in the form of cost-sharing, were also identified as significant factors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

WE-A-16A-01: International Medical Physics Symposium: Increasing Access to Medical Physics Education/Training and Research Excellence

In response to a world in which cancer is a growing global health challenge, there is now a greater need for US Medical Physicists and other Radiation Oncology professionals across institutions to work together and be more globally engaged in the fight against cancer. There are currently many opportunities for Medical Physicists to contribute to alleviating this pressing need, especially in helping enhance access to Medical Physics Education/training and Research Excellence across international boundaries, particularly for low and middle-income countries (LMIC), which suffer from a drastic shortage of accessible knowledge and quality training programs in radiotherapy. Many Medical Physicists are not aware of the range of opportunities that even with small effort could have a high impact. Faculty at the two CAMPEP-accredited Medical Physics Programs in New England: the University of Massachusetts Lowell and Harvard Medical School have developed a growing alliance to increase Access to Medical Physics Education/training and Research Excellence (AMPERE), and facilitate greater active involvement of U.S. Medical Physicists in helping the global fight against cancer and cancer disparities. In this symposium, AMPERE Alliance members and partners from Europe and Africa will present and discuss the growing global cancer challenge, the dearth of knowledge, research, and other barriers to providing life-saving radiotherapy in LMIC, mechanisms for meeting these challenges, the different opportunities for participation by Medical Physicists, including students and residents, and how participation can be facilitated to increase AMPERE for global health. Learning Objectives: To learn about the growing global cancer challenge, areas of greatest need and limitations to accessing knowledge and quality radiotherapy training programs, especially in LMIC; To learn about the range of opportunities for Medical Physicists, including students and residents, to work together in global health to help increase AMPERE and alleviate the growing global burden of cancer; To present and discuss a new model for harmonizing Medical Physics Training across countries and how this model (UMass and Heidelberg) could be extended to LMIC in collaboration with the IAEA; To highlight a new platform and program for facilitating contributions by Medical Physicists to increase AMPERE towards the elimination of global cancer disparities. Challenges in Cancer Control in Africa Twalib A. Ngoma, MD, Professor, Executive Director, Ocean Road Cancer Institute, Dar Es Salaam, Tanzania Cancer care in Africa is beset by lack of attention, political will, cancer registries, cancer plans, human resources, financial resources and treatment facilities.. As a result of this, cancer patients in Africa are far more likely to die of their disease than those in developed countries. According to data from the WHO 750,000 new cancer cases occur in Africa every year and this number is predicted to rise by 70% by 2020. To make matters worse, an estimated 75% of cancer patients in Africa have advanced or incurable cancers at diagnosis making palliative care the most realistic approach to their management. Furthermore, Cancer prevention is nearly nonexistent, cancer detection is rare and treatment usually comes too late and is inefficient. The overall mortality-to-incidence ratio for men with cancer in the Africa is 0.75 compared with 0.54 in the developed world while the ratios for women in Africa, is 0.65 compared with 0.45 for women in the developed world. There is also limited access to radiotherapy. According to the International Atomic Energy Agency (IAEA), whilst developed countries usually have one radiotherapy machine per 250,000 people, most African nations have only one machine per ten million people. The above numbers are alarming and speak for themselves. The only solution to improve this alarming situation is to address the major challenges which African countries face in provision of cancer services which include but not limited to lack of cancer registries, lack of funding, lack of human resources, lack of radiotherapy machines, lack of cancer drugs and lack of accessible and affordable cancer screening, early diagnosis, treatment or palliative care services. Since there are considerable differences among African countries, in my presentation I will share with the audience how we address cancer control challenges in Tanzania in general and specifically in radiation oncology. The African continent cancer plan 2013 2017 Folakemi Odedina, PhD, Professor and Director of Health Disparities, UF Health Cancer Center, University of Florida The burden of cancer is rising in Africa, in addition to current heavy burden of communicable, and other non-cancer related non—communicable diseases. Conquering cancer in Africa will require a comprehensive collaborative approach with cancer clinicians, scientists, patients, advocates, policy makers and community leaders working hand-in-hand at the local, state, national, and continent levels with the primary mission: To reduce the number of deaths from cancer and improve the quality of life of cancer patients, survivors and caregivers. Unfortunately, less than 40% of African countries have a credible cancer control policy and program. The African Organization for Research and Training in Cancer (AORTIC) decided to create an African Cancer Plan to provide cost-effective strategies that can be employed throughout the continent to fight cancer. Based on the African proverb that “It takes a village to raise a child”, the Cancer Plan provides specific strategies that can be used by individuals, employers, organizations and policy-makers to fight cancer. In addition, we have provided overarching strategies to address cancer in Africa and targeted 5-year plan for prostate, breast, cervix, lung and liver cancers. In developing this Cancer Plan, our primary goal is to decrease cancer incidence and mortality in Africa. This goal can only be achieved by stakeholders and dedicated individuals to lead and implement the strategies outlined in this plan. If you are interested in partnering with AORTIC to reduce the burden of cancer in Africa, please send an email to info@aortic-africa.org. Synergies in research and clinical care through international collaboration Thomas Bortfeld and David Gierga, Massachusetts General Hospital, Harvard Medical School, MA Medical Physics relies on high technology that is not distributed equally. The whole spectrum of Medical Physics technologies is not available at every hospital or research institute, and not even in every high income country. One example is heavy ion therapy equipment which is currently only available in Japan, Germany and Italy. There is also a large global variation in terms of research infrastructure and focus. A student of Medical physics cannot gain broad experience, certainly not hands-on experience, by staying at one place only. While it is debatable what a good trade-off between breadth and depth in Medical Physics education is, it is generally agreed upon that some breadth is necessary. Researchers in Medical Physics have to cross borders if they need specific technologies for their projects. Therefore it is self-evident that international programs in Medical Physics education and research make sense. Yet, very few programs of this type exist. In this presentation we will report on our own experience of pursuing an international career in Medical Physics, with international student programs, and with the international exchange of researchers. We will present new or planned opportunities such as the medical beamline at CERN in Geneva. We will also report on the synergies in clinical care through international collaborations between partners in high and low income countries. One example is the partnership of the MGH/Harvard Medical School community with the oncology community and government of Botswana to form the BOTSOGO (BOTSwana Oncology Global Outreach) initiative. This collaborative effort in oncology care was spurred by existing relationships in HIV/AIDS research and care delivery developed within the Botswana-Harvard AIDS Institute Partnership (BHP). The initial efforts of the BOTSOGO initiative have been organized as follows: 1) on-site visits to share expertise in clinical cancer care for capacity building purposes (e.g. cervical brachytherapy), 2) developing a forum for multi-disciplinary case discussions and education and 3) relationship building with local stakeholders for long-term sustainability and growth. An international system for the certification of medical physicists Raymond K. Wu, Chairman, IOMP Professional Relations Committee; Chairman, AAPM Exchange Scientist Program Subcommittee An international system for the certification of medical physicists is an important issue. The International Organization for Medical Physicists (IOMP) has in collaboration with a number of member countries established the International Medical Physics Certification Board (IMPCB) to address this issue, and to provide a mechanism to mark the milestone for the professional development of clinical medical physicists. Raymond Wu, PhD, is the CEO of IMPCB and the Chairman of the IOMP Professional Relations Committee. He is the invited speaker recommended by IOMP to give a talk on this important subject. He will give the latest update of the work of IMPCB, its near term goals, and pathways to the goals. He will also discuss the importance of such an International System of certification in the training/education of next generation Medical Physicists, including those in low and middle income countries (LMIC) where such training is crucial in the fight against cancer. Learning Objectives: Understand the certification program as described in the IOMP Policy Statements. Understand the plan of the IMPCB to establish the accreditation process of national certification programs. Understand the goals of this international collaborative effort and the potential impacts to the quality of clinical medical physics practice. Medical Physics Education Across Continents: The UMass Lowell and Heidelberg University Joint Coordination Effort Erno Sajo, Director of Medical Physics, University of Massachusetts at Lowell Medical Physics education has unique flavors across institutions within the US and shows significant differences across continents. In the latter, even the definition of Medical Physics may differ. Not only is there a difference in topical coverage, but often what is considered a cohesive topic in one institution, and taught as a single course, is fragmented among several other courses in the other institution due to a different philosophy. Because of the regulatory and certification requirements, these differences impact the mobility of medical physicists across continents. As a result, physicists who wish to practice in the US or Canada but have completed their education elsewhere often find that they have to take remedial courses or even obtain a new degree in Medical Physics despite the fact that they already have one. Outreach to developing countries, therefore, is even more difficult. The University of Massachusetts Lowell and Heidelberg University recently completed a joint coordination effort, in which they identified topics that are common versus complementary in their medical physics curricula. A student exchange program was developed that permits students to take any of the common topics at the other institution while taking complementary courses as electives, which count towards their degree requirements at their home institution. Thesis research is also mutually accepted. When properly documented, in this way CAMPEP recommendations can be met across the institutions. Therefore, students participating in this program satisfy both the American Board of Radiology (ABR) requirements and the European regulatory requirements. The framework on which this collaboration rests and the cross-comparison methods developed therein may be implemented in other exchange programs and thus a similar approach can be adopted in outreach programs with developing countries. IAEA PACT Program and opportunities for support and collaboration Susan Morgan, Program Coordinator, International Atomic Energy Agency, Vienna, Austria In response to the developing world's cancer crisis, the International Atomic Energy Agency (IAEA) established the Program of Action for Cancer Therapy (PACT) in 2004 to fully realize the public health impact obtained through global partnerships in cancer control and technology transfer in radiation medicine. PACT's vision strives for global partnerships to confront the cancer crisis in developing countries, notably with our sister United Nations agency, the World Health Organization (WHO), and our Joint Programme on Cancer Control established in 2009. The IAEA, through PACT, the WHO, the International Agency for Research on Cancer (IARC) and other cancer-related organizations work together to make a coordinated global response in supporting low and middle income (LMI) IAEA Member States in the implementation of comprehensive national cancer control programmes. PACT's goals are: To build global partnerships of cancer-related organizations committed to addressing the challenge of cancer in LMI Member States in all its aspects; To mobilize resources from charitable trusts, foundations, and others in public and private sectors sources to assist LMI Member States to develop and implement their radiation medicine capacities within a national cancer control programme (NCCP); and, To ensure the effective and sustainable transfer of radiation medicine technologies or knowledge to all LMI Member States where unmet needs exist. PACT work focuses on: imPACT: Assessing Cancer Burden PMDS: Developing Global Partnerships VUCCnet: Promoting Cancer Control Training AGaRT: Making Radiotherapy Accessible Facilitating increased participation and professional development of Medical Physicists and other Radiation Oncology professionals in global health Wilfred Ngwa, Harvard Medical School, University of Massachusetts Lowell, MA The 2014 World Health Organization (WHO) Cancer report highlights an alarming increase in the global burden of cancer. It also highlights what it terms “the cancer divide”, or disparities, evinced by a substantially higher cancer burden in low and middle income countries (LMIC) in Asia, Central/South America and Africa. The WHO even predicts a potential African cancer epidemic by 2020 if significant progress is not made in global cancer control efforts. Evidence that collaborative global health approaches have led to major progress in controlling infectious diseases including in LMIC suggests that similar approaches will be useful for non-communicable diseases like cancer. In consonance with this, leaders in cancer policy from the USA and 14 economically diverse countries recently concluded that successful campaigns to control cancers with existing methods and to improve current strategies will increasingly depend onconcerted multinational collaborations (Sci Transl Med 5, p. 175, 2013). Hence there is growing urgency for increasing collaborative global cancer Care Research and Education (CaRE), as well as support for greater effectiveness of already existing initiatives involving partners from different nations, diverse economic and cultural backgrounds. The good news is that there is a growing awareness of the importance of global health and growing interest including amongst Medical Physicists and other Radiation oncology (RadOnc) professionals to participate in global health. However, many are unaware of currently existing opportunities for participation that even with small effort could have a high impact. Over 50% of cancer patients in the developed world depend on RadOnc professionals for their treatment, and hence participation of RadOnc professionals in global health efforts in the global fight against cancer is crucial. It is also important that the next generation of RadOnc professionals (students, and residents) be trained with a global perspective, to be global health leaders in cancer CaRE. This presentation will highlight a novel platform for enhancing participation and professional development of Medical Physicists and other RadOnc professionals in global health. Ways in which this platform can facilitate contributions by Medical Physicists and other RadOnc Professionals, students and residents in global health towards the elimination of global cancer disparities will be discussed. This will be followed by a panel discussion by some of the pioneers/leaders in collaborative global cancer CaRE on the growing cancer burden, challenges and opportunities for greater active involvement and professional development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Evaluating community solar as a measure to promote equitable clean energy access

Rooftop and community solar are alternative product classes for residential solar in the United States. Community solar, where multiple households buy solar from shared systems, could make solar more accessible by reducing initial costs and removing adoption barriers for renters and multifamily building occupants. Here we test whether community solar has expanded solar access in the United States. On the basis of a sample of 11 states, we find that community solar adopters are about 6.1 times more likely to live in multifamily buildings than rooftop solar adopters, 4.4 times more likely to rent and earn 23% less annual income. In this study, we do not find that community solar expands access in terms of race. These differences are driven, roughly evenly, by inherent differences between the two solar products and by policies to promote low-income community solar adoption. The results suggest that alternative solar products can expand solar access and that policy could augment such benefits.

14 SOLAR ENERGY↗
DOE OSTI2017

Adapting Community Impact Assessment for Nuclear Waste Transportation - 17273

As the United States develops a consent-based approach for an interim storage facility for nuclear waste, it is clear that the impacts on corridor communities will have to be assessed. The Yucca Mountain Program established a requirement for assessing impacts on communities. In order to achieve consent, impact assessment will have to be part of a transportation plan. Conventional transportation planners have developed a process for assessing the impacts on communities that occur as the result of transportation projects. This Process-Community Impact Assessment (CIA) has been widely adopted throughout the United States. This paper suggests ways in which CIA can be adapted from conventional transportation planning to the problem of spent nuclear fuel. This paper uses the CIA as 'an iterative process to evaluate the effects of a transportation action on a community and its quality of life.' This paper describes the community impact assessment process as it would be adapted for spent nuclear fuel transportation. The paper lists common impacts attributable to transportation projects and whether or not these would be applicable for this process. The paper describes the legal basis for assessing these impacts and shows how early commencement of an impact process helps ensure that transportation policies and investments include the concerns of affected communities. Conducting an assessment of this type leads to an understanding of the relationship between transportation actions and the community. Such an understanding can minimize conflict and resolve potential problems. Underlying this process is the idea that assessments that include the active participation of affected parties, leads to better decisions and greater acceptance of projects, while enhancing agency credibility. The paper defines 'community' as it applies in this case and describes the process that can be used to perform an assessment of this type. The paper concludes that a process of this type can facilitate a successful siting decision making and accelerate community acceptance that is necessary for a successful transportation program. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Climate policy implications of nonlinear decline of Arctic land permafrost and other cryosphere elements

Arctic feedbacks accelerate climate change through carbon releases from thawing permafrost and higher solar absorption from reductions in the surface albedo, following loss of sea ice and land snow. Here, we include dynamic emulators of complex physical models in the integrated assessment model PAGE-ICE to explore nonlinear transitions in the Arctic feedbacks and their subsequent impacts on the global climate and economy under the Paris Agreement scenarios. The permafrost feedback is increasingly positive in warmer climates, while the albedo feedback weakens as the ice and snow melt. Combined, these two factors lead to significant increases in the mean discounted economic effect of climate change: +4.0% (24.8 trillion) under the 1.5 °C scenario, +5.5% ($33.8 trillion) under the 2 °C scenario, and +4.8% (66.9 trillion) under mitigation levels consistent with the current national pledges. Considering the nonlinear Arctic feedbacks makes the 1.5 °C target marginally more economically attractive than the 2 °C target, although both are statistically equivalent.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Multi-level impacts of climate change and supply disruption events on a potato supply chain: An agent-based modeling approach

Context: The world is experiencing frequent extreme weather events like droughts, snowstorms, and shifting of seasons due to climate change. Increased frequency and severity of these extreme weather events threaten food security because agriculture depends on climate conditions. Impacts of climate change on the agricultural system not only occur at the grower’s level, but also cascade to other levels along the supply chain. Objective: In this study, we aim to quantify a wide range of economic impacts of different extreme climate events on different stages of a food supply chain. Methods: We chose the potato supply chain in Idaho as a case study. We developed a multi-echelon supply chain simulation model using an agent-based modeling (ABM) approach with five types of agents—farmers, shippers, processors, retailers, and logistics companies. In addition to the business-as-usual (BAU) scenario, we designed two climate-related disruption events—drought and snowstorm. We quantified the heterogeneous impacts at different stages of the supply chain for both fresh and processed potatoes using key performance indicators (KPIs) including revenues, prices, lead times, traded quantities, and food waste quantity. Results and Conclusion: The impacts of the disruption events are different on different agents in the supply chain for different product categories. The price hike of fresh potatoes is far higher than processed potatoes during disruption events. This price hike makes consumers switch to processed potatoes, which require more fresh potatoes as an input that further reinforces the price hike. However, because processed potatoes have an elastic demand, once their prices go up due to higher input cost, their demand drops. Non-contracted farmers gain additional revenues from the disruption events, whereas contracted farmers incur a loss due to lock-in price and lower than usual harvest. Significance: The methodology developed in this study could be applied to other food and agricultural supply chains for understanding the vulnerabilities at agent levels due to climate change disruption events. Furthermore, the findings would help develop mitigation strategies or policies to improve the well-being of the overall supply chain.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The role of information structures in game-theoretic multi-agent learning

Multi-agent learning (MAL) studies how agents learn to behave optimally and adaptively from their experience when interacting with other agents in dynamic environments. The outcome of a MAL process is jointly determined by all agents’ decision-making. Hence, each agent needs to think strategically about others’ sequential moves, when planning future actions. The strategic interactions among agents makes MAL go beyond the direct extension of single-agent learning to multiple agents. With the strategic thinking, each agent aims to build a subjective model of others decision-making using its observations. Such modeling is directly influenced by agents’ perception during the learning process, which is called the information structure of the agent’s learning. As it determines the input to MAL processes, information structures play a significant role in the learning mechanisms of the agents. This review creates a taxonomy of MAL and establishes a unified and systematic way to understand MAL from the perspective of information structures. Here we define three fundamental components of MAL: the information structure (i.e., what the agent can observe), the belief generation (i.e., how the agent forms a belief about others based on the observations), as well as the policy generation (i.e., how the agent generates its policy based on its belief). In addition, this taxonomy enables the classification of a wide range of state-of-the-art algorithms into four categories based on the belief-generation mechanisms of the opponents, including stationary, conjectured, calibrated, and sophisticated opponents. We introduce Value of Information (VoI) as a metric to quantify the impact of different information structures on MAL. Finally, we discuss the strengths and limitations of algorithms from different categories and point to promising avenues of future research.

97 MATHEMATICS AND COMPUTING↗