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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

North American Carbon Project (NACP) Regional Interim Synthesis: Terrestrial Biospheric Model Intercomparison

Understanding of carbon exchange between terrestrial ecosystems and the atmosphere can be improved through direct observations and experiments, as well as through modeling activities. Terrestrial biosphere models (TBMs) have become an integral tool for extrapolating local observations and understanding to much larger terrestrial regions. Although models vary in their specific goals and approaches, their central role within carbon cycle science is to provide a better understanding of the mechanisms currently controlling carbon exchange. Recently, the North American Carbon Program (NACP) organized several interim-synthesis activities to evaluate and inter-compare models and observations at local to continental scales for the years 2000 to 2005. Here, we compare the results from the TBMs collected as part of the regional and continental interim-synthesis (RCIS) activities. The primary objective of this work is to synthesize and compare the 19 participating TBMs to assess current understanding of the terrestrial carbon cycle in North America.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

FutureGen 2.0 Monitoring Program: An Overview of the Monitoring Approach and Technologies Selected for Implementation

The FutureGen 2.0 Project will design and build a first-of-its-kind, near-zero emissions coal-fueled power plant with carbon capture and storage (CCS). To assess storage site performance and meet the regulatory requirements of the Class VI Underground Injection Control (UIC) Program for CO2 Geologic Sequestration, the FutureGen 2.0 project will implement a suite of monitoring technologies designed to 1) evaluate CO2 mass balance and 2) detect any unforeseen loss in CO2 containment. The monitoring program will include direct monitoring of the injection stream and reservoir, and early-leak-detection monitoring directly above the primary confining zone. It will also implement an adaptive monitoring strategy whereby monitoring results are continually evaluated and the monitoring network is modified as required, including the option to drill additional wells in out-years. Wells will be monitored for changes in CO2 concentration and formation pressure, and other geochemical/isotopic signatures that provide indication of CO2 or brine leakage. Indirect geophysical monitoring technologies that were selected for implementation include passive seismic, integrated surface deformation, time-lapse gravity, and pulsed neutron capture logging. Near-surface monitoring approaches that have been initiated include surficial aquifer and surface- water monitoring, soil-gas monitoring, atmospheric monitoring, and hyperspectral data acquisition for assessment of vegetation conditions. Initially, only the collection of baseline data sets is planned; the need for additional near- surface monitoring will be continually evaluated throughout the design and operational phases of the project, and selected approaches may be reinstituted if conditions warrant. Given the current conceptual understanding of the subsurface environment, early and appreciable impacts to near-surface environments are not expected.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Model Predictive Control of Discrete-Continuous Energy Systems via Generalized Disjunctive Programming

Generalized Disjunctive Programming (GDP) provides an alternative framework to model optimization problems with both discrete and continuous variables. The key idea behind GDP involves the use of logical disjunctions to represent discrete decisions in the continuous space, and logical propositions to denote algebraic constraints in the discrete space. Compared to traditional mixed-integer programming (MIP), the inherent logic structure in GDP yields tighter relaxations that are exploited by global branch and bound algorithms to improve solution quality. In this paper, we present a general GDP model for optimal control of hybrid systems that exhibit both discrete and continuous dynamics. Specifically, we use GDP to formulate a model predictive control (MPC) model for piecewise-affine systems with implicit switching logic. As an example, the GDP-based MPC approach is used as a supervisory control to improve energy efficiency in residential buildings with binary on/off, relay-based thermostats. A simulation study is used to demonstrate the validity of the proposed approach, and the improved solution quality compared to existing MIPbased control approaches.

Bhattacharya, Arnab↗
DOE OSTI2013

A Profile of Academic Training Program Directors and Chairs in Radiation Oncology

Purpose: To identify objective characteristics and benchmarks for program leadership in academic radiation oncology. Methods and Materials: A study of the 87 Accreditation Council for Graduate Medical Education radiation oncology training program directors (PD) and their chairs was performed. Variables included age, gender, original training department, highest degree, rank, endowed chair assignment, National Institutes of Health (NIH) funding, and Hirsch index (H-index). Data were gathered from online sources such as departmental websites, NIH RePORTER, and Scopus. Results: There were a total of 87 PD. The median age was 48, and 14 (16%) were MD/PhD. A total of 21 (24%) were female, and rank was relatively equally distributed above instructor. Of the 26 professors, at least 7 (27%) were female. At least 24 (28%) were working at the institution from which they had received their training. A total of 6 individuals held endowed chairs. Only 2 PD had active NIH funding in 2012. The median H-index was 12 (range, 0-51) but the index dropped to 9 (range, 0-38) when those who served as both PD and chair were removed from the group. A total of 76 chairs were identified at the time of the study. The median age was 55, and 9 (12%) were MD/PhD. A total of 7 (9%) of the chairs were female, and rank was professor for all with the exception of 1 who was listed as “Head” and was an associate professor. Of the 76 chairs, at least 10 (13%) were working at the institution from which they received their training. There were a total of 21 individuals with endowed chairs. A total of 13 (17%) had NIH funding in 2012. The median H-index was 29 (range, 3-60). Conclusions: These data provide benchmarks for individuals and departments evaluating leadership positions in the field of academic radiation oncology. Such data are useful for evaluating leadership trends over time and comparing academic radiation oncology with other specialties.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

A global stochastic programming approach for the optimal placement of gas detectors with nonuniform unavailabilities

Optimal design of a gas detection systems is challenging because of the numerous sources of uncertainty, including weather and environmental conditions, leak location and characteristics, and process conditions. Rigorous CFD simulations of dispersion scenarios combined with stochastic programming techniques have been successfully applied to the problem of optimal gas detector placement; however, rigorous treatment of sensor failure and nonuniform unavailability has received less attention. To improve reliability of the design, this paper proposes a problem formulation that explicitly considers nonuniform unavailabilities and all backup detection levels. The resulting sensor placement problem is a large-scale mixed-integer nonlinear programming (MINLP) problem that requires a tailored solution approach for efficient solution. We have developed a multitree method which depends on iteratively solving a sequence of upper-bounding master problems and lower-bounding subproblems. The tailored global solution strategy is tested on a real data problem and the encouraging numerical results indicate that our solution framework is promising in solving sensor placement problems. This study was selected for the special issue in JLPPI from the 2016 International Symposium of the MKO Process Safety Center.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Preparation of single-crystal spherical γ-Mo{sub 2}N by temperature-programmed reaction between β-MoO{sub 3} and NH{sub 3}

In the present wok, single-crystalline spherical γ-Mo{sub 2}N powders was successfully prepared by the temperature-programmed reaction of single-crystal spherical β-MoO{sub 3} with NH{sub 3} in the temperature ranges of 1013–1073 K. Herein, the Mo source used was monoclinic system, β-MoO{sub 3}, a metastable phase of MoO{sub 3}. It is found that the characterizations of the as-prepared γ-Mo{sub 2}N powders are strongly depended on the selection of the MoO{sub 3} precursor. In other words, the as-prepared γ-Mo{sub 2}N powders inherited the shape, size and structure of the used β-MoO{sub 3} precursors upon reaction with NH{sub 3}. In order to make a comparison, β-MoO{sub 3} was also reduced by the mixed gases of N{sub 2} and H{sub 2} with the flow rate ratio of 1:3 at the identical conditions. It was found that pure β-Mo{sub 2}N polycrystalline can be obtained when the temperature was 1013 K; while further increasing the reaction temperature, metal Mo powder will be turned up. - Highlights: • Metastable phase β-MoO{sub 3} was used to prepare Mo{sub 2}N via temperature-programmed reaction. • Single-crystal spherical γ-Mo{sub 2}N can be obtained by reducing Single-crystal spherical β-MoO{sub 3} with NH{sub 3}. • The as-prepared γ-Mo{sub 2}N inherited the morphology and size of β-MoO{sub 3} precursors. • β-Mo{sub 2}N can be obtained if using the N{sub 2}-H{sub 2} mixed gases. • The morphologies of β-Mo{sub 2}N had no heredity with the parent MoO{sub 3}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Detector requirements and simulation results for the EIC exclusive, diffractive and tagging physics program using the ECCE detector concept

This article presents a collection of simulation studies using the ECCE detector concept in the context of the EIC’s exclusive, diffractive, and tagging physics program, which aims to further explore the rich quark–gluon structure of nucleons and nuclei. To successfully execute the program, ECCE proposed to utilize the detector system close to the beamline to ensure exclusivity and tag ion beam/fragments for a particular reaction of interest. Preliminary studies confirm the proposed technology and design satisfy the requirements. Further, the projected physics impact results are based on the projected detector performance from the simulation at 10 or 100 fb -1 of integrated luminosity. Additionally, insights related to a potential second EIC detector are documented, which could serve as a guidepost for future development.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2011

Tuning collective communication for Partitioned Global Address Space programming models

Partitioned Global Address Space (PGAS) languages offer programmers the convenience of a shared memory programming style combined with locality control necessary to run on large-scale distributed memory systems. Even within a PGAS language programmers often need to perform global communication operations such as broadcasts or reductions, which are best performed as collective operations in which a group of threads work together to perform the operation. In this study we consider the problem of implementing collective communication within PGAS languages and explore some of the design trade-offs in both the interface and implementation. In particular, PGAS collectives have semantic issues that are different than in send–receive style message passing programs, and different implementation approaches that take advantage of the one-sided communication style in these languages. We present an implementation framework for PGAS collectives as part of the GASNet communication layer, which supports shared memory, distributed memory and hybrids. The framework supports a broad set of algorithms for each collective, over which the implementation may be automatically tuned. In conclusion, we demonstrate the benefit of optimized GASNet collectives using application benchmarks written in UPC, and demonstrate that the GASNet collectives can deliver scalable performance on a variety of state-of-the-art parallel machines including a Cray XT4, an IBM BlueGene/P, and a Sun Constellation system with InfiniBand interconnect.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

The Jefferson Lab program: From 6 GeV operations to the 12 GeV upgrade

The Thomas Jefferson National Laboratory and the CEBAF accelerator operated for more than a decade, running a comprehensive scientific program that improved our understanding of the strong interaction. The facility is now moving toward an upgrade of the machine, from 6 to 12 GeV; a new experimental hall will be added and the equipment of the three existing halls will be enhanced. In this contribution some selected results from the rich physics program run at JLab, as well as the prospects for the near future, will be presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Multi-parametric analysis for mixed integer linear programming: An application to transmission upgrade and congestion management

Upgrading the capacity of existing transmission lines is essential for meeting the growing energy demands, facilitating the integration of renewable energy, and ensuring the security of the transmission system. This study focuses on the selection of lines whose capacities and by how much should be expanded from the perspective of the Independent System Operators (ISOs) to minimize the total system cost. We employ advanced multi-parametric programming and an enhanced branch-and-bound algorithm to address complex mixed-integer linear programming (MILP) problems, considering multi-period time constraints and physical limitations of generators and transmission lines. To characterize the various decisions in transmission expansion, we model the increased capacity of existing lines as parameters within a specified range. This study first relaxes the binary variables to continuous variables and applies the Lagrange method and Karush-Kuhn-Tucker (KKT) conditions to obtain optimal solutions and identify critical regions associated with active and inactive constraints. Moreover, we extend the traditional branch-and-bound (B&B) method by determining the problem’s upper and lower bounds at each node of the B&B decision tree, helping to manage computational challenges in large-scale MILP problems. Here, we compare the difference between the upper and lower bounds to obtain an approximate optimal solution within the decision-makers’ tolerable error range. In addition, the first derivative of the objective function on the parameters of each line is used to inform the selection of lines for easing congestion and maximizing social welfare. Finally, the capacity upgrades are selected by weighing the reductions in system costs against the expense of upgrading line capacities. The findings are supported by numerical simulations and provide transmission-line planners with decision-making guidance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Assessing the Returns to Land and Greenhouse Gas Savings from Producing Energy Crops on Conservation Reserve Program Land

Using land already enrolled in the Conservation Reserve Program (CRP) in the eastern region of the U.S. for producing energy crops for bioenergy while reducing land rental payments offers the potential for lowering the program costs, increasing returns to CRP landowners, and displacing greenhouse gas (GHG) emissions from fossil fuels. We develop an integrated modeling approach to analyze the combination of biomass prices and CRP land rental payment reductions that can incentivize energy crop production on CRP land and its potential to increase soil carbon stocks and displace fossil fuel emissions. Here, we find that conversion of 3.4 million ha in the CRP can be economically viable at a minimum biomass price of 75 Mg –1 with full CRP land rental payment or at 100 Mg –1 with 75% of this land rental payment; this conversion can result in savings of 0.52 and 1.25 billion Mg CO 2 -eq in life-cycle emissions through the displacement of energy-equivalent fossil fuels and coal-based electricity, respectively, and an additional 0.11 billion Mg CO 2 -eq soil carbon sequestration relative to the status quo, with CRP left unharvested over the 2016–2030 period. The soil carbon debt due to the transition from unharvested CRP land to energy crops is short-lived and more than offset by the reduction in fossil fuel emissions. The net discounted benefits from producing energy crops on CRP land through a reduced need for government payments to maintain existing enrollment, higher returns to CRP landowners, and the value of the reduction in GHG emissions could be as high as 16–30 billion by using them for cellulosic biofuels to displace gasoline and 35–68 billion by displacing coal-based electricity over the 2016–2030 period if biomass prices are 75–125 Mg –1 and land rental payments are reduced by 25%.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Benders Decomposition Using Graph Modeling and Multi-Parametric Programming

Benders decomposition is a widely used method for solving large and structured optimization problems, but its performance is affected by the repeated solution of subproblems. We propose a flexible and modular algorithmic framework for accelerating Benders decomposition. Specifically, we express the problem structure by using a graph-theoretic modeling abstraction in which nodes represent optimization subproblems and edges represent connectivity between subproblems. A key innovation of our approach is that we embed multiparametric programming (mp) surrogates for node subproblems, which maps the exact analytical map of the subproblem solution space. The use of mp surrogates allows us to replace subproblem solves with fast look-ups and function evaluations for primal and dual variables during the iterative Benders process. We formally show the equivalence between classical Benders cuts and those derived from the mp solution. We implement our framework in the open-source PlasmoBenders.jl software package. To demonstrate the capabilities of the proposed framework, we apply it to a two-stage stochastic programming problem, which aims to make optimal capacity expansion decisions under market uncertainty. We evaluate both single-cut and multicut variants of Benders decomposition and show that the use of mp surrogates achieves substantial speedups in subproblem solve time, while preserving the convergence guarantees of Benders decomposition. We highlight advantages in solution analysis and interpretability that is enabled by mp critical region tracking; specifically, we show that these reveal how decisions evolve geometrically across the Benders search. Our results aim to demonstrate that combining surrogate modeling with graph modeling offers a promising and extensible foundation for structure-exploiting decomposition. In addition, by decomposing the problem into more tractable subproblems, the proposed approach also aims to overcome scalability issues of mp. Finally, the use of mp surrogates provides a unifying and modular optimization framework that enables the representation of heterogeneous node subproblems as modeling objects with a homogeneous structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Navigating Large Chemical Spaces Using Graph Theory and Integer Programming

Navigating and analyzing large chemical spaces are necessary to accelerate the design and discovery of new molecules and chemical processes. In this work, we introduce a computational framework that integrates graph theory and integer programming to enable the efficient navigation of large chemical spaces. Our framework represents the chemical space as a graph, wherein nodes represent molecules and edges represent the degree of similarity or connectivity based on domain-specific information. Using the graph representation, we identify representative molecules by computing the so-called minimum dominating set (MDS), which in our context is the minimum set of molecules that is connected to all other molecules. We present a suite of solution strategies for the MDS problem including heuristic and rigorous integer programming (IP) approaches. We show that these approaches allow us to capture physicochemical properties and domain-specific logic and constraints, facilitating the identification of molecules with the target properties. We demonstrate the effectiveness of the proposed approach by navigating the chemical space of per- and polyfluoroalkyl substances (PFAS); this comprises approximately 15,000 molecular structures. We compare our framework against traditional dimensionality reduction and clustering methods such as t-SNE and K-means clustering.

Chemical structure↗
DOE OSTI2021

Defect-Enabled Phase Programming of Transition Metal Dichalcogenide Monolayers

The ability to tune the local electronic transport properties of group VI transition metal dichalcogenide (TMD) monolayers by strain-induced structural phase transformations (“phase programming”) has stimulated much interest in the potential applications of such layers as ultrathin programmable and dynamically switchable nanoelectronics components. In this manuscript, we propose a new approach toward controlling TMD monolayer phases by employing macroscopic in-plane strains to amplify heterogeneous strains arising from tailored, spatially extended defects within the monolayer. Furthermore, the efficacy of our proposed approach is demonstrated via numerical simulations of emerging domains localized around arrays of holes, grain boundaries, and compositional heterointerfaces. Quantitative relations between the macroscopic strains required, spatial resolution of domain patterns, and defect configurations are developed. In particular, the introduction of arrays of holes is identified as the most feasible phase programming route.

2D materials↗
DOE OSTI2024

Nanoscale Ferroelectric Programming of van der Waals Heterostructures

We demonstrate an approach to creating nanoscale potentials in van der Waals layers integrated with a buried programmable ferroelectric layer. Using ultra-low-voltage electron beam lithography (ULV-EBL), we can program the ferroelectric polarization in Al 1–x B x N (AlBN) thin films, generating structures with sizes as small as 35 nm. We demonstrate the ferroelectric field effect with a graphene/vdW stack on AlBN by creating a p–n junction. This resist-free, high-resolution, contactless patterning method offers a new pathway to integrate ferroelectric films with a wide range of two-dimensional layers including transition-metal dichalcogenides (TMD), enabling arbitrary programming and top-down creation of multifunctional devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Unconventional isoquinoline-based SERMs elicit fulvestrant-like transcriptional programs in ER+ breast cancer cells

Estrogen receptor alpha (ERα) is a ligand-dependent master transcriptional regulator and key driver of breast cancer pathology. Small molecule hormones and competitive antagonists favor unique ERα conformational ensembles that elicit ligand-specific transcriptional programs in breast cancer and other hormone-responsive tissues. By affecting disparate ligand binding domain structural features, unconventional ligand scaffolds can redirect ERα genomic binding patterns to engage novel therapeutic transcriptional programs. To improve our understanding of these ERα structure-transcriptional relationships, we develop a series of chemically unconventional antagonists based on the antiestrogens elacestrant and lasofoxifene. High-resolution x-ray co-crystal structures show that these molecules affect both classical and unique structural motifs within the ERα ligand binding pocket. They show moderately reduced antagonistic potencies on ERα genomic activities but are effective anti-proliferative agents in luminal breast cancer cells. Interestingly, they favor a 4-hydroxytamoxifen-like accumulation of ERα in breast cancer cells but lack uterotrophic activities in an endometrial cell line. Importantly, RNA sequencing shows that the lead molecules engage transcriptional pathways similar to the selective estrogen receptor degrader fulvestrant. This advance shows that fulvestrant-like genomic activities can be achieved without affecting ERα accumulation in breast cancer cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

The human body at cellular resolution: the NIH Human Biomolecular Atlas Program

Transformative technologies are enabling the construction of three dimensional (3D) maps of tissues with unprecedented spatial and molecular resolution. Over the next seven years, the NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) aims to develop a widely accessible framework for comprehensively mapping the human body at single-cell resolution by supporting technology development, data acquisition, and detailed spatial mapping. HuBMAP will integrate its efforts with other funding agencies, programs, and the biomedical research community at large towards the shared vision of a comprehensive, accessible 3D molecular and cellular atlas of the human body, in health and various disease settings.

59 BASIC BIOLOGICAL SCIENCES↗