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DOE OSTI2013

Improving the Assessment and Valuation of Climate Change Impacts for Policy and Regulatory Analysis

The social cost of carbon (SCC) is a monetized metric for evaluating the benefits associated with marginal reductions in carbon dioxide (CO2) emissions. It represents the expected welfare loss from the future damages caused by the release of one tonne of CO2 in a given year, expressed in consumption equivalent terms. It is intended to be a comprehensive measure, taking into account changes in agricultural productivity, human health risks, loss of ecosystem services and biodiversity, and the frequency and severity of flooding and storms, among other possible impacts. Estimating the SCC requires long-term modeling of global economic activity, the climate system, and the linkages between the two through anthropogenic greenhouse gas (GHG) emissions and the effects of changing climatic conditions on economic activity and human well-being. The United States government currently uses the SCC in regulatory benefit-cost analyses to assess the welfare effects of changes in CO2 emissions. Consistent application of the SCC to federal rulemaking analyses began in 2009-2010 with the development of a set of global SCC estimates that employed three prominent integrated assessment models (IAMs) -- DICE, FUND, and PAGE. The U.S. government report identified a number of limitations associated with SCC estimates in general and its own assumptions in particular: an incomplete treatment of damages, including potential “catastrophic” impacts; uncertainty regarding the extrapolation of damage functions to high temperatures; incomplete treatment of adaptation and technological change; and the evaluation of uncertain outcomes in a risk-neutral fashion. External experts have identified other potential issues, including how best to model long-term socio-economic and emissions pathways, oversimplified physical climate and carbon cycle modeling within the IAMs, and an inconsistency between non-constant economic growth scenarios and constant discount rates. The U.S. government has committed to updating the estimates regularly as modeling capabilities and scientific and economic knowledge improves. To help foster further improvements in estimating the SCC, the U.S. Environmental Protection Agency and the U.S. Department of Energy hosted a pair of workshops on “Improving the Assessment and Valuation of Climate Change Impacts for Policy and Regulatory Analysis.” The first focused on conceptual and methodological issues related to integrated assessment modeling and the second brought together natural and social scientists to explore methods for improving damage assessment for multiple sectors. These two workshops provide the basis for the 13 papers in this special issue.

Climate Change↗
DOE OSTI2022

What can simulation test beds teach us about social science? Results of the ground truth program

The ground truth program used simulations as test beds for social science research methods. The simulations had known ground truth and were capable of producing large amounts of data. This allowed research teams to run experiments and ask questions of these simulations similar to social scientists studying real-world systems, and enabled robust evaluation of their causal inference, prediction, and prescription capabilities. We tested three hypotheses about research effectiveness using data from the ground truth program, specifically looking at the influence of complexity, causal understanding, and data collection on performance. We found some evidence that system complexity and causal understanding influenced research performance, but no evidence that data availability contributed. The ground truth program may be the first robust coupling of simulation test beds with an experimental framework capable of teasing out factors that determine the success of social science research.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Explaining and predicting human behavior and social dynamics in simulated virtual worlds: reproducibility, generalizability, and robustness of causal discovery methods

Ground Truth program was designed to evaluate social science modeling approaches using simulation test beds with ground truth intentionally and systematically embedded to understand and model complex Human Domain systems and their dynamics Lazer et al. (Science 369:1060–1062, 2020). Our multidisciplinary team of data scientists, statisticians, experts in Artificial Intelligence (AI) and visual analytics had a unique role on the program to investigate accuracy, reproducibility, generalizability, and robustness of the state-of-the-art (SOTA) causal structure learning approaches applied to fully observed and sampled simulated data across virtual worlds. In addition, we analyzed the feasibility of using machine learning models to predict future social behavior with and without causal knowledge explicitly embedded. In this paper, we first present our causal modeling approach to discover the causal structure of four virtual worlds produced by the simulation teams—Urban Life, Financial Governance, Disaster and Geopolitical Conflict. Our approach adapts the state-of-the-art causal discovery (including ensemble models), machine learning, data analytics, and visualization techniques to allow a human-machine team to reverse-engineer the true causal relations from sampled and fully observed data. We next present our reproducibility analysis of two research methods team’s performance using a range of causal discovery models applied to both sampled and fully observed data, and analyze their effectiveness and limitations. We further investigate the generalizability and robustness to sampling of the SOTA causal discovery approaches on additional simulated datasets with known ground truth. Our results reveal the limitations of existing causal modeling approaches when applied to large-scale, noisy, high-dimensional data with unobserved variables and unknown relationships between them. We show that the SOTA causal models explored in our experiments are not designed to take advantage from vasts amounts of data and have difficulty recovering ground truth when latent confounders are present; they do not generalize well across simulation scenarios and are not robust to sampling; they are vulnerable to data and modeling assumptions, and therefore, the results are hard to reproduce. Finally, when we outline lessons learned and provide recommendations to improve models for causal discovery and prediction of human social behavior from observational data, we highlight the importance of learning data to knowledge representations or transformations to improve causal discovery and describe the benefit of causal feature selection for predictive and prescriptive modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Reactive transport benchmarks for subsurface environmental simulation

Over the last 20 years, we have seen firsthand the evolution of multicomponent reactive transport modeling and the expanding range and increasing complexity of subsurface applications it is being used to address. There is a growing reliance on reactive transport modeling (RTM) to address some of the most compelling issues facing our planet: climate change, nuclear waste management, contaminant remediation, and pollution prevention. While these issues are motivating the development of new and improved capabilities for subsurface environmental modeling using RTM (e.g., biogeochemistry from cell-scale physiology to continental-scale terrestrial ecosystems, nonisothermal multiphase conditions, coupled geomechanics), there remain longstanding challenges in characterizing the natural variability of hydrological, biological, and geochemical properties in subsurface environments and limited success in transferring models between sites and across scales. An equally important trend over the last 20 years is the evolution of modeling from a service sought out after data has been collected to a multifaceted research approach that provides (1) an organizing principle for characterization and monitoring activities; (2) a systematic framework for identifying knowledge gaps, developing and integrating new knowledge; and (3) a mechanistic understanding that represents the collective wisdom of the participating scientists and engineers. There are now large multidisciplinary projects where the research approach is model-driven, and the principal product is a holistic predictive simulation capability that can be used as a test bed for alternative conceptualizations of processes, properties, and conditions. Much of the future growth and expanded role for RTM will depend on its continued ability to exploit technological advancements in the earth and environmental sciences. Advances in measurement technology, particularly in molecular biology (genomics), isotope fractionation, and high-resolution X-ray spectroscopy, have created new lines of research that can be used to inform the conceptualization of reactions and rate laws and validate mechanistic models. For example, spectroscopy has identified the oxidation states of key components and elemental distributions at increasingly smaller scales and lower concentrations; molecular biology has progressed from identifying the presence of microbes to characterization of which microbial communities are active and what they are doing (i.e., microbial function), which has led in turn to the identification of active processes under conditions beyond what analytical chemistry can discern; isotope ratios in pore water and solid phases that can be used to distinguish between biotic from abiotic processes, sorption from precipitation, and origin and age of groundwater. The other noteworthy development that is expanding the role of RTM in subsurface environmental modeling is he advance in computational technology that is enabling the simulation of more coupled processes with increasing mechanistic detail. In some cases, this involves the inclusion of more reactive species and/or microbial populations in the simulations; in other cases, the impact is through the ability to achieve high resolution of property distributions over longer simulated times. To achieve these ambitious objectives for subsurface reactive transport simulation, the subsurface science and engineering community is being driven to provide accurate assessments of engineering performance and risk for important issues with far-reaching consequences. As a result, the complexity and detail of subsurface processes, properties, and conditions that can be simulated have significantly expanded. This expansion was enabled, in part, by advances in measurement technology, computing technology, and numerical techniques.

benchmarking↗
DOE OSTI2016

Preface to the Special Issue: Strategic Opportunities for Fusion Energy

Here, the Journal of Fusion Energy provides a forum for discussion of broader policy and planning issues that play a crucial role in energy fusion programs. In keeping with this purpose and in response to several recent strategic planning efforts worldwide, this Special Issue on Strategic Opportunities was launched with the goal to invite fusion scientists and engineers to record viewpoints of the scientific opportunities and policy issues that can drive continued advancements in fusion energy research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Stellarator Research Opportunities: A Report of the National Stellarator Coordinating Committee

This paper is the product of a stellarator community workshop, organized by the National Stellarator Coordinating Committee and referred to as Stellcon, that was held in Cambridge, Massachusetts in February 2016, hosted by MIT. The workshop was widely advertised, and was attended by 40 scientists from 12 different institutions including national labs, universities and private industry, as well as a representative from the Department of Energy. The final section of this document describes areas of community wide consensus that were developed as a result of the discussions held at that workshop. Areas where further study would be helpful to generate a consensus path forward for the US stellarator program are also discussed. The program outlined in this document is directly responsive to many of the strategic priorities of FES as articulated in “Fusion Energy Sciences: A Ten-Year Perspective (2015–2025)” [1]. The natural disruption immunity of the stellarator directly addresses “Elimination of transient events that can be deleterious to toroidal fusion plasma confinement devices” an area of critical importance for the US fusion energy sciences enterprise over the next decade. Another critical area of research “Strengthening our partnerships with international research facilities,” is being significantly advanced on the W7-X stellarator in Germany and serves as a test-bed for development of successful international collaboration on ITER. Finally, this report also outlines how materials science as it relates to plasma and fusion sciences, another critical research area, can be carried out effectively in a stellarator. Additionally, significant advances along two of the Research Directions outlined in the report; “Burning Plasma Science: Foundations—Next-generation research capabilities”, and “Burning Plasma Science: Long pulse—Sustainment of Long-Pulse Plasma Equilibria” are proposed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Large-scale optimization-based non-negative computational framework for diffusion equations: Parallel implementation and performance studies

It is well-known that the standard Galerkin formulation, which is often the formulation of choice under the finite element method for solving self-adjoint diffusion equations, does not meet maximum principles and the non-negative constraint for anisotropic diffusion equations. Recently, optimization-based methodologies that satisfy maximum principles and the non-negative constraint for steady-state and transient diffusion-type equations have been proposed. To date, these methodologies have been tested only on small-scale academic problems. The purpose of this paper is to systematically study the performance of the non-negative methodology in the context of high performance computing (HPC). PETSc and TAO libraries are, respectively, used for the parallel environment and optimization solvers. For large-scale problems, it is important for computational scientists to understand the computational performance of current algorithms available in these scientific libraries. The numerical experiments are conducted on the state-of-the-art HPC systems, and a single-core performance model is used to better characterize the efficiency of the solvers. Furthermore, our studies indicate that the proposed non-negative computational framework for diffusion-type equations exhibits excellent strong scaling for real-world large-scale problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

On the Validity of Linear Response Theory in High-Dimensional Deterministic Dynamical Systems

This theoretical work considers the following conundrum: linear response theory is successfully used by scientists in numerous fields, but mathematicians have shown that typical low-dimensional dynamical systems violate the theory’s assumptions. Here we provide a proof of concept for the validity of linear response theory in high-dimensional deterministic systems for large-scale observables. We introduce an exemplary model in which observables of resolved degrees of freedom are weakly coupled to a large, inhomogeneous collection of unresolved chaotic degrees of freedom. By employing statistical limit laws we give conditions under which such systems obey linear response theory even if all the degrees of freedom individually violate linear response. We corroborate our result with numerical simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

State of practice and emerging application of analytical techniques of nuclear forensic analysis: highlights from the 4th Collaborative Materials Exercise of the Nuclear Forensics International Technical Working Group (ITWG)

Founded in 1996 upon the initiative of the “Group of 8” governments (G8), the Nuclear Forensics International Technical Working Group (ITWG) is an ad hoc organization of official nuclear forensics practitioners (scientists, law enforcement, and regulators) that can be called upon to provide technical assistance to the global community in the event of a seizure of nuclear or radiological materials. The ITWG is supported by and is affiliated with roughly 40 countries and international partner organizations including the International Atomic Energy Agency (IAEA), EURATOM, INTERPOL, EUROPOL, and the United Nations Interregional Crime and Justice Research Institute (UNICRI). Besides providing a network of nuclear forensics laboratories that are able to assist law enforcement during a nuclear smuggling event, the ITWG is also committed to the advancement of the science of nuclear forensic analysis, largely through participation in periodic table top and Collaborative Materials Exercises (CMXs). Exercise scenarios use “real world” samples with realistic forensics investigation time constraints and reporting requirements. These exercises are designed to promote best practices in the field and test, evaluate, and improve new technical capabilities, methods and techniques in order to advance the science of nuclear forensics. The ITWG recently completed its fourth CMX in the 20 year history of the organization. This was also the largest materials exercise to date, with participating laboratories from 16 countries or organizations. Three samples of low enriched uranium were shipped to these laboratories as part of an illicit trafficking scenario, for which each laboratory was asked to conduct nuclear forensic analyses in support of a fictitious criminal investigation. An objective review of the State Of Practice and Art of international nuclear forensic analysis based upon the outcome of this most recent exercise is provided.

ITWG CMX-4↗
DOE OSTI2019

Changing the Rules of the Game: Used Fuel Studies Outside of a Remote Handling Facility

Recent advances in micro-fabrication tools like the FEI Helios NanoLab 660 dual Focused Ion Beam (FIB) and Scanning Electron Microscope (SEM) now make it possible to easily and reliably prepare micron (or smaller) specimens for analyses or further experimentation. Pacific Northwest National Laboratory (PNNL) has leveraged this capability at the Category II Nuclear Facility, the Radiochemical Processing Laboratory, to facilitate nuclear materials analysis and experimentation of used nuclear fuel. Micron-scale specimens of un-irradiated UO2 fuel pellets of various enrichments from depleted to 4.95% enriched, relative to 235U, were prepared at PNNL and shipped to the University of Missouri’s Research Reactor (MURR) for irradiation. Prior to shipping, samples were attached to commercially available Transmission Electron Microscopy half-grids via ion deposition, which were then housed in specially designed aluminum sample holders approved for use at the reactor facility. This minimized handling and preparation requirements prior to materials analysis after irradiation. Samples were irradiated to a burnup equivalent of 8 – 3,700 MWd/MTU. Additionally, by reducing the size of the specimens, and therefore their emitted radiation dose, the required cooling time after irradiation and prior to analysis was greatly diminished, and handling of these samples could proceed outside of a hot cell facility. Results from these experiments provided insight into the initial production of noble metal phase particles in used nuclear fuel at extremely low burnup levels. Some incompatibility with the container was observed at higher burnup. Micro-scale irradiation experiments were performed at roughly 1/7th of the time, effort and expense a similar bulk-scale study requiring a shielded hot cell facility would require. Conducting nuclear materials analysis at the micron-scale holds the promise of enhancing collaboration and material accessibility to the broader research community, improving accessibility to cutting edge research tools by the nuclear materials science community, lowering the risk to the scientist by reducing radiation dose and exposure, reducing facility and research costs associated with the requirement to conduct nuclear materials science within glovebox or remote handling facilities, and minimizing waste.

Schwantes, Jon M.↗
DOE OSTI2024

Cultural Shifts in High Energy Physics Collaboration from the Cold War to the Present: A Historical and Philosophical Perspective

Here, this article employs empirical history and the philosophy of science to study cultural convergences and divergences in international collaborations in high energy physics. We examine two cases: (1) E-36, an experiment on small angle proton-proton scattering conducted during the Cold War at the National Accelerator Laboratory (NAL) in the USA by Soviet and US scientists and (2) an ongoing collaborative experiment, NICA, at the Joint Institute for Nuclear Research (JINR, Dubna), which is a project devoted to heavy-ion physics. The JINR, particularly its Laboratory of High Energy Physics (formerly the “Laboratory of High Energies”) is the main mediating actor between these two cases (i.e., E-36 and NICA), as the majority of Soviet participants in E-36 were representatives of the Institute. Using empirical data collected through archival searches, field observations conducted at JINR in 2018–2019, and in-depth interviews, we tell a story of cultural differences in high energy physics by applying the concepts of ‘trading zones’ (P. Galison) and the translation of interests in actor-networks (B. Latour, M. Callon and others). We analyze three types of cultural diversity (specialization, nationality, and generational) in light of the implications of temporal context and the dichotomy between East and West, showing the roles cultural diversity plays in scientific collaboration (which is an integral part of as well as obstacle to scientific research that can nevertheless provide learning opportunities). Our study aims to demonstrate how disunity and diversity may function in scientific research and how high energy physics collaborations can remain productive despite sometimes deep divergences, including those between East and West.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

The simulation on absorption properties of metamaterial/GaAs/electrode layer hybrid structure based Terahertz photoconductive detector

Terahertz (THz) photodetectors have attracted great attention from scientists worldwide for their application in security checking, biomedical treatment and astronomical observation of remote stars and distant galaxies. As a typical THz detector, extrinsic GaAs based photoconductive detector is facing critical technical bottlenecks in the epitaxial growth of sufficiently thick and high-quality GaAs absorption layer. In this work, a novel THz photoconductive detector based on metamaterial/GaAs/electrode layer hybrid structure was designed and simulated. By setting the periodic split ring resonator (SRR) structure as 88 μm pitch with 8 μm width, the absorption peaks exist at the wavelength of about 142 and 367 μm, which originate from the resonant cavity and the SRR dipole resonance effect, and the novel device shows a significant enhancement compared with the conventional GaAs photoconductive detector. Thus, the necessary thickness of GaAs absorption-layer is largely reduced, and the resonant absorption peak can be modulated by changing the thickness of absorption layer. This work provides a novel device structure which can solve the critical epitaxial growth bottleneck of GaAs photoconductive detector and used for the astronomical observation, security check, etc.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Advances in Coupling of Kinetics and Molecular Scale Tools to Shed Light on Soil Biogeochemical Processes

Biogeochemical processes in soils such as sorption, precipitation, and redox play critical roles in the cycling and fate of nutrients, metal(loid)s and organic chemicals in soil and water environments. Advanced analytical tools enable soil scientists to track these processes in real-time and at the molecular scale. Our review focuses on recent research that has employed state-of-the-art molecular scale spectroscopy, coupled with kinetics, to elucidate the mechanisms of nutrient and metal(loid) reactivity and speciation in soils. We found that by coupling kinetics with advanced molecular and nano-scale tools major advances have been made in elucidating important soil chemical processes including sorption, precipitation, dissolution, and redox of metal(loids) and nutrients. Such advances will aid in better predicting the fate and mobility of nutrients and contaminants in soils and water and enhance environmental and agricultural sustainability.

58 GEOSCIENCES↗
DOE OSTI2017

The contributions of 49ers to the measurements and models of ultrafast photosynthetic energy transfer

Progress in measuring and understanding the mechanism of the elementary energy transfer steps in photosynthetic light harvesting from roughly 1949 to the present is sketched with a focus on the group of scientists born in 1949 ± 1. Improvements in structural knowledge, laser spectroscopic methods, and quantum dynamical theories have led to the ability to record and calculate with reasonable accuracy the timescales of elementary energy transfer steps. The importance of delocalized excited states and of near-field Coulombic coupling is noted. The microscopic understanding enables consistent coarse graining and should enable a much-improved understanding of the regulation of photosynthetic light harvesting.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Tribute to Kenneth Sauer (1931–2022): a mentor, a role-model, and an inspiration to all in the field of photosynthesis

Abstract Kenneth (Ken) Sauer was a mainstay of research in photosynthesis at the University of California, Berkeley and the Lawrence Berkeley National Laboratory (LBNL) for more than 50 years. Ken will be remembered by his colleagues, and other workers in the field of photosynthesis as well, for his pioneering work that introduced the physical techniques whose application have enriched our understanding of the basic reactions of oxygenic photosynthesis. His laboratory was a training ground for many students and postdocs who went on to success in the field of photosynthesis and many others. Trained as a physical chemist, he always brought that quantitative approach to research questions and used several spectroscopic methods in his research. His broad scientific interests concerned the role of manganese in oxygen evolution, electronic properties of chlorophylls, energy transport in antenna complexes, and electron transport reactions. He was also an enthusiastic teacher, an enormously successful mentor who leaves behind a legion of scientists as his abiding legacy, a lover of music and the outdoors with many interests beyond science, and a dedicated family man with a great sense of humility. In this tribute, we summarize some aspects of Ken Sauer’s life and career, illustrated with selected research achievements, and describe his approach to research and life as we perceived it, which is complemented by reminiscences of several current researchers in photosynthesis and other fields. The supporting material includes Ken Sauers’s CV and publication list, as well as a list of the graduate students and postdocs he trained and of researchers that spent a sabbatical in his lab.

Plant Sciences↗
DOE OSTI2021

Expert Text Analysis in the Inclusion of History and Philosophy of Science in Higher Education

The history and philosophy of science (HPS) plays a special role in education. An elective HPS course onthe philosophy of scientific experimentation for young scientists and graduate students of natural scienceis presented. The course bears a pragmatic character, and its main aims include the development of criticalthinking (CT), familiarization with philosophical problems in the relevant areas of knowledge, and thecultivation of a taste for reflective, critical analysis, both individual and group-based, which contributes todeeper understanding of the features of scientific practice in the context of modern complex groupcooperation. Students are offered a classical HPS program that included debates on the relationship betweenempiricism and rationalism, the role of Kant’s transcendental philosophy, modern topics associated withthe practical success of rationalism in the emergence of modern natural science, and the theory-ladennessof experimentation. Particular attention during the course is paid to the problems of megascience, theinclusion of which is justified by the specifics of the students’ engagement with science, technology,engineering, and mathematics (STEM). Emphasis is placed on the structure and typology of the collectivesubject in the modern educational process as well as in experimental practice. Lessons on the methodologyof expert text analysis (META), which are aimed at the development of critical thinking skills and thecreation of an interdisciplinary discussion space, are included in the course and relied on the example ofthe history and philosophy of high energy physics to motivate professional reflection. META classesincluded in the course prepare graduate students for teamwork in big science, proto-megascience, andmegascience. The course offers practical recommendations that could be applied to students’ own researchand could be useful for practitioners.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Outstanding Questions and Future Research on Magnetic Reconnection

This short article highlights unsolved problems of magnetic reconnection in collisionless plasma. Advanced in-situ plasma measurements and simulations have enabled scientists to gain a novel understanding of magnetic reconnection. Nevertheless, outstanding questions remain concerning the complex dynamics and structures in the diffusion region, cross-scale and regional couplings, the onset of magnetic reconnection, and the details of particle energization. We discuss future directions for magnetic reconnection research, including new observations, new simulations, and interdisciplinary approaches.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

The Surface-Topography Challenge: A Multi-Laboratory Benchmark Study to Advance the Characterization of Topography

Surface performance is critically influenced by topography in virtually all real-world applications. The current standard practice is to describe topography using one of a few industry-standard parameters. The most commonly reported number is Ra, the average absolute deviation of the height from the mean line (at some, not necessarily known or specified, lateral length scale). However, other parameters, particularly those that are scale-dependent, influence surface and interfacial properties; for example the local surface slope is critical for visual appearance, friction, and wear. The present Surface-Topography Challenge was launched to raise awareness for the need of a multi-scale description, but also to assess the reliability of different metrology techniques. In the resulting international collaborative effort, 153 scientists and engineers from 64 research groups and companies across 20 countries characterized statistically equivalent samples from two different surfaces: a “rough” and a “smooth” surface. The results of the 2088 measurements constitute the most comprehensive surface description ever compiled. We find wide disagreement across measurements and techniques when the lateral scale of the measurement is ignored. Consensus is established through scale-dependent parameters while removing data that violates an established resolution criterion and deviates from the majority measurements at each length scale. Our findings suggest best practices for characterizing and specifying topography. The public release of the accumulated data and presented analyses enables global reuse for further scientific investigation and benchmarking.

42 ENGINEERING↗