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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Predictive modeling of a subcritical pulverized-coal power plant for optimization: Parameter estimation, validation, and application

As renewable power generation deployment increases, fossil fuel plants are increasingly required to operate more flexibly. Many coal-fired power plants were originally designed to operate at base load and do not operate optimally at partial load. Predictive first-principles plant-wide models can be employed to identify opportunities for flexibility improvements and diagnose low-load operating issues. This paper describes the application of the Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES) to model and optimize flexible power plant operations. The key benefits of using IDAES are that it provides an open-source, fully equation-oriented modeling framework for efficient modular model construction, reuse, and customization, together with a mathematical optimization framework leveraging powerful, state-of-the-art solvers. The process systems engineering workflow from predictive process simulation to parameter estimation, model validation, and plant optimization is applicable to a variety of existing and next-generation energy systems as well as other chemical and environmental processes. Here, to demonstrate this capability, a physics-based, steady-state model was developed to improve full- and part-load performance of the Escalante Generating Station, a 245 MWe (net) subcritical pulverized coal-fired power plant owned and operated by Tri-State Generation and Transmission Association. Specifically, sixty-nine model parameters were simultaneously estimated from several months of operating data enabling prediction of flow rates, temperatures, pressures, and steam quality throughout the plant. The validated model was leveraged by Escalante to reduce the minimum operating load from 90 MW to 50 MW by diagnosing a low-load water-hammer issue, enabling coal usage and emissions reductions during periods of low power demand. Additionally, opportunities for heat rate reduction (i.e., efficiency improvement) through a steeper sliding-pressure approach to load-following and optimization of other boiler operating variables were also identified and quantified. For example, a potential efficiency improvement of 0.7 percentage points was observed at half-load operation.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2023

Advances in benchmarking and round robin testing for PEM water electrolysis: Reference protocol and hardware

While the number of publications in the PEM water electrolysis community increases each year, no common ground concerning reference hardware (test cells and test bench) and testing protocols has been yet established. This would, however, be necessary for the comparability of experimental results. First attempts for such reference hardware and procedures have been made in the framework of the Task 30 Electrolysis within the Technology Collaboration Programme on Advanced Fuel Cells (AFC TCP) of the International Energy Agency (IEA). Since then, improvements of both the test hardware (test cell and components) as well as the measurement protocol were identified, and a revised methodology and key results based on a comprehensive measurement series have been obtained. A detailed protocol for testing commercial reference components with a reference laboratory test cell developed in-house by Fraunhofer ISE is presented. For evaluation of the protocol and the hardware, it was tested at three different institutions at the same time. Impedance spectroscopic and polarization data was acquired and analyzed. The obtained differences in performance were calculated to give the community an expectation window to compare own data to. Finally, the importance of a thorough temperature control and the conditioning phase are demonstrated.

08 HYDROGEN↗

DOE OSTI2022

Determination of the 161 Tb half-life

There is significant interest in the use of terbium radioisotopes for applications in cancer therapy and diagnosis. Of these, 161 Tb, a medium energy beta- and prolific auger emitter, is being investigated as a potential alternative to 177 Lu. The higher proportion of conversion electron and Auger electron emissions, and variety of low-energy gammas make 161 Tb an attractive targeted theranostic. As a product of nuclear fission, 161 Tb is also of importance to nuclear forensics. The current evaluated half-life of 6.89(2) d has a standard uncertainty that contributes significantly to the standard uncertainty of decay calculated activity determination. Furthermore, the accuracy of this evaluated half-life has been called into question by measurements reported recently at the Institute of Radiation Physics (IRP), Switzerland. In this work, the half-life of 161 Tb was measured at three independent laboratories located in the United Kingdom and United States of America for a total of five determinations using three independent measurement techniques. In conclusion, the half-life determined for 161 Tb of 6.9637(29) d confirms the observed 1 % relative increase observed by IRP, though the reported half-lives in this work and at IRP are significantly different (ζ-score = 3.1).

half-life↗

DOE OSTI2020

The moving target of visualization software for an increasingly complex world

Visualization has evolved into a mature scientific field and it has also become widely accepted as a standard approach in diverse fields, including physics, life sciences, and business intelligence. However, despite its successful development, there are still many open research questions that require customized implementations in order to explore and establish concepts, and to perform experiments and take measurements. Many methods and tools have been developed and published but most are stand-alone prototypes and have not reached a mature state that can be used in a reliable manner by collaborating domain scientists or a wider audience. In this study, we discuss the challenges, solutions, and open research questions that affect the development of sophisticated, relevant, and novel scientific visualization solutions with minimum overheads. Furthermore, we summarize and discuss the results of a recent National Institute of Informatics Shonan seminar on these topics.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Genomic materials design: CALculation of PHAse Dynamics

The CALPHAD system of fundamental phase-level databases, now known as the Materials Genome, has enabled a mature technology of computational materials design and qualification that has already met the acceleration goals of the national Materials Genome Initiative. Here, as first commercialized by QuesTek Innovations, the methodology combines efficient genomic-level parametric design of new material composition and process specifications with multidisciplinary simulation-based forecasting of manufacturing variation, integrating efficient uncertainty management. Recent projects demonstrated under the multi-institutional CHiMaD Design Center notably include novel alloys designed specifically for additive manufacturing. With the proven success of the CALPHAD-based Materials Genome technology, current university research emphasizes new methodologies for affordable accelerated expansion of more accurate CALPHAD databases. Rapid adoption of these new capabilities by US apex corporations has compressed the materials design and development cycle to under 2 years, enabling a new “materials concurrency” integrated into a new level of concurrent engineering supporting an unprecedented level of manufacturing innovation.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Tailoring Microbial Fitness Through Computational Steering and CRISPRi-Driven Robustness Regulation

The widespread application of genetically modified microorganisms (GMMs) across diverse sectors underscores the pressing need for robust strategies to mitigate the risks associated with their potential uncontrolled escape. This study merges computational modeling with CRISPR interference (CRISPRi) to refine GMM metabolic robustness. Utilizing ensemble modeling, we achieved high-throughput in silico screening for enzymatic targets susceptible to expression alterations. Translating these insights, we developed functional CRISPRi, boosting fitness control via multiplexed gene knockdown. Our method, enhanced by an insulator-improved gRNA structure and an off-switch circuit controlling a compact Cas12m, resulted in rationally engineered strains with escape frequencies below National Institutes of Health standards. The effectiveness of this approach was confirmed under various conditions, showcasing its ability for secure GMM management. This research underscores the resilience of microbial metabolism, strategically modifying key nodes to halt growth without provoking significant resistance, thereby enabling more reliable and precise GMM control. A record of this paper's transparent peer review process is included in the supplemental information.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Fe Kα XANES, Fe Kβ HERFD XANES and EPMA flank method determinations of the oxidation state of Fe in garnet

The ferric to total iron ratios (Fe 3+ /ΣFe) of garnets can be paired with thermodynamic mineral activity models to quantify the oxygen fugacity of garnet-bearing rocks. However, techniques with a high analytical and spatial resolution are necessary to distinguish differences in garnet Fe 3+ /ΣFe ratios at the percent level and to accurately measure garnets that are zoned or contain inclusions. We acquired conventional Fe Kα and high-resolution energy fluorescence detection (HERFD) Fe Kβ X-ray absorption near edge structure (XANES) spectra and electron microprobe flank method analyses on a suite of 27 peridotitic and eclogitic garnets with Fe 3+ /ΣFe ratios previously determined by Mössbauer spectroscopy to evaluate the precision of each technique. We examined variations in the energy and intensity of three XANES spectral features as a function of Fe 3+ /ΣFe ratios: 1) the intensity ratio of two-post edge features (I-ratio; Fe Kα only); 2) the energy of the Fe edge at 90% normalized intensity (E 0.9 ; Fe Kα only) and 3) the pre-edge centroid energy (Fe Kα and HERFD Fe Kβ). In accordance with previous work, we find the energies of garnet pre-edge centroids are relatively insensitive to Fe 3+ /ΣFe ratios. The I-ratios of peridotitic and eclogitic garnets are offset from each other at low Fe 3+ /ΣFe ratios (≤0.13); I-ratio garnet XANES calibrations are composition-specific. The E 0.9 feature is independent of garnet major element composition in spectra that have been corrected for the effects of self-absorption. We produce two Fe Kα garnet XANES calibrations based on variations in the E0.9 feature; one calibration with all garnet reference materials included (Fe 3+ /ΣFe up to 1.0; “all garnet calibration”) and another calibration specific to garnets with low Fe 3+ /ΣFe ratios (“low ferric calibration”). Fe 3+ /ΣFe ratios calculated from the mean of up to 25 flank method measurements on eight garnet reference materials fall within 4% absolute of a one-to-one correlation with Fe 3+ /ΣFe ratios measured by Mössbauer. The standard error of the mean Fe 3+ /ΣFe ratio calculated from flank method approaches the Mössbauer-determined Fe 3+ /ΣFe ratio within estimated error (3%) after three analyses. Flank method precision is enhanced at higher beam current; however, the precision of the flank method does not approach the precision of XANES under any microprobe analytical condition tested here. Garnet reference materials detailed here are available by request to the Smithsonian Institution.

58 GEOSCIENCES↗

DOE OSTI2020

Phase field benchmark problems targeting fluid flow and electrochemistry

Here, we continue our development of phase field model benchmark problems with the addition of a third set, complimenting our previously developed problems for diffusion, precipitation, dendritic growth and linear elasticity. These benchmark problems are being jointly developed by the Center for Hierarchical Materials Design (CHiMaD) and the National Institute of Standards and Technology (NIST) along with input from the phase field community. The first problem in this third set targets Stokes flow, with a particular emphasis on flow around an obstruction placed asymmetrically in the domain. While Stokes flow is not traditionally in the canon of phase field problems, it is a class of problems gaining importance in areas such as filtration and water purification. The second problem deals with coupled Cahn-Hilliard diffusion and electrostatic forces, which is an important area in energy storage and battery sciences. We present our own solutions and discuss sources of numerical errors for the Stokes problem as well as simple checks to avoid fundamental issues in the coupled diffusion-electrostatics problem. The latter problem contains some subtleties that we expand on in an Appendix.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Jacobian-based model diagnostics and application to equation oriented modeling of a carbon capture system

It can be difficult to identify the specific variables or equations responsible for convergence issues in large mathematical programming models. The Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES-IP) contains a tool to identify poorly scaled constraints and variables by searching for rows and columns of the Jacobian matrix with small L2-norms. A singular value decomposition is then performed to identify degenerate sets of equations and remaining scaling issues. Here, this work presents a flowsheet developed for post-combustion carbon capture using a monoethanolamine (MEA) solvent system as a case study. This work takes the reader through the entire process of model diagnostics and reformulation, from a basic introduction to the mathematics behind these model diagnostics to the reformulations necessary to make the model numerically robust, including a significantly modified enhancement factor model.

IDAES↗

DOE OSTI2023

Methodology for physics-informed generation of synthetic neutron time-of-flight measurement data

Accurate neutron cross section data are a vital input to the simulation of nuclear systems for a wide range of applications from energy production to national security. The evaluation of experimental data is a key step in producing accurate cross sections. There is a widely recognized lack of reproducibility in the evaluation process due to its artisanal nature and therefore there is a call for improvement within the nuclear data community. This can be realized by automating/standardizing viable parts of the process, namely, parameter estimation by fitting theoretical models to experimental data. This automation effort could greatly benefit from a synthetic data resource. This work leverages problem-specific physics, Monte Carlo sampling, and a general methodology for data synthesis to generate unlimited, labelled experimental cross-section data that is statistically indistinguishable to the observed data. Heuristic and, where applicable, rigorous statistical comparisons to observed data support this claim. The demonstration is based on/limited to transmission measurements at Rensselaer Polytechnic Institute (RPI) and energy-differential cross sections in the resolved resonance region (RRR). An open-source software is published alongside this article that executes the complete methodology to produce high-utility synthetic datasets. The goal of this work is to provide an approach and corresponding tool that will allow the evaluation community to begin exploring more data-driven, ML-based solutions to long-standing challenges in the field.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Digitalization of an experimental electrochemical reactor via the smart manufacturing innovation platform

The exponential increase in data produced over the last two decades has revolutionized the way we collect, store, process, analyze, model, and interpret information to improve profitability. Manufacturing is no exception. How- ever, Smart Manufacturing, the digital practice, organization, workforce, and infrastructure transformation for collection and deployment of data and models at scale and at all levels of manufacturing, is a complex, costly, and labor-intensive journey that is still seeing slow adoption. The Clean Energy Smart Manufacturing Innovation Institute (CESMII), a national Manufacturing USA public-private partnership sponsored by the Department of Energy, is addressing this scaled use of data and modeling in manufacturing. CESMII has focused on how to col- lect and use operating data for numerous applications that improve productivity, precision, and performance of manufacturing operations from factory floor to supply chain using process simulation, predictive analytics, mon- itoring and control, and real-time optimization. Because contextualized data are key, CESMII has developed the Smart Manufacturing Innovation Platform (SMIP) to lower the barriers to the data that are needed to accelerate data-based model building, improve data visualization, and more quickly gain insights. Reusable, standards-based ways of doing data collection, ingestion, and contextualization are particularly important for scaling access and use of data. The SMIP uses a standards-based definition and construct for reusable information models called an SM Profile. When an SM Profile is used in conjunction with the SMIP, the SMIP ensures the availability of contextualized, operational data for model building. The present work demonstrates Smart Manufacturing and the application of the SMIP for building several data-centered models for the operation and control of an ex- perimental electrochemical reactor that reduces carbon dioxide (CO 2 ) gas to valuable liquid and gas chemicals, such as alcohols, olefins, and syngas. We describe how the SMIP plays a central role in more effective model building and we demonstrate how the electochemical reactor can be controlled and optimized for the desired products. Use of the SMIP involves the transmission of real-time sensor measurements to a cloud resource so that the operating data are available to all model building experts. The data collection and transmission process is fully automated to greatly reduce the need for manual manipulation of the data. Data-driven machine learning models are used for advanced real-time state estimation, real-time optimization, and model-based feedback control for the reactor. The application models are implemented as a system to monitor the data flow and control the electrochemical reactor with a single visualization interface. SM Profiles are used to demonstrate reusability of the information models for the reactor and the instrumentation. The application packages, algorithms, and user interfaces developed are cast as Docker images in a library to facilitate reusability of the application models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Process intensification education contributes to sustainable development goals. Part 1

In 2015 all the United Nations (UN) member states adopted 17 sustainable development goals (UN-SDG) as part of the 2030 Agenda, which is a 15-year plan to meet ambitious targets to eradicate poverty, protect the environment, and improve the quality of life around the world. Although the global community has progressed, the pace of implementation must accelerate to reach the UN-SDG time-line. For this to happen, professionals, institutions, companies, governments and the general public must become cognizant of the challenges that our world faces and the potential technological solutions at hand, including those provided by chemical engineering. Process intensification (PI) is a recent engineering approach with demonstrated potential to significantly improve process efficiency and safety while reducing cost. It offers opportunities for attaining the UN-SDG goals in a cost-effective and timely manner. However, the pedagogical tools to educate undergraduate, graduate students, and professionals active in the field of PI lack clarity and focus. This paper sets out the state-of-the-art, main discussion points and guidelines for enhanced PI teaching, deliberated by experts in PI with either an academic or industrial background, as well as representatives from government and specialists in pedagogy gathered at the Lorentz Center (Leiden, The Netherlands) in June 2019 with the aim of uniting the efforts on education in PI and produce guidelines. In this Part 1, we discuss the societal and industrial needs for an educational strategy in the framework of PI. The terminology and background information on PI, as it relates to educational implementation in industry and academia, are provided as a preamble to Part 2, which presents practical examples that will help educating on Process Intensification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Modeling the effect of habitat availability and quality on endangered winter-run Chinook salmon ( Oncorhynchus tshawytscha ) production in the Sacramento Valley

Reconciliation between water uses and sustaining aquatic species populations requires an effort to identify and quantify essential habitat characteristics for ecosystem health and valuation methods to predict ecosystem response to restoration actions. This process is particularly challenging for anadromous fish species such as California's Sacramento River winter-run Chinook salmon, due to their limited geographic range and diverse life history habitat requirements. Tools, such as life-cycle models, are needed to manage population dynamics and quantify the composite effects of processes across space and time. Nevertheless, complex institutions can hinder result interpretation and communication, and limit model use in decision-making. This paper focuses on the federally endangered and endemic Sacramento River winter-run Chinook (Oncorhynchus tshawytscha) by developing a Winter-Run Habitat-based Population Model (WRHAP). Additionally, WRHAP is a conceptual, freshwater rearing stage model that includes alternative rearing habitats reported in the literature (e.g., floodplains, off-channel and tributaries), defines rules of habitat use based on instream conditions, and incorporates a juvenile growth module that combines bioenergetics modeling with empirical growth rates. Model outputs reasonably follow observed out-migration patterns and provide a realistic smolt size distribution arriving at the San Francisco Bay. This effort demonstrates the importance of currently “non-critical” habitats (as defined by the Endangered Species Act) for juvenile development, with floodplain habitat contributing to a quarter of out-migrating biomass (despite < 18% availability and <10% of total rearing days), and off-channel growth being one of the most sensitive parameters (explaining ~13% of average juvenile weight variance). The model shows the utility of a simple population model to explore relationships between habitat quality/quantity and juvenile development, and to assist water/environmental management and decision-making processes focused on species recovery.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Farmer characteristics and decision-making: A model for bioenergy crop adoption

We report the commercial development of biofuels and bioproducts depends on whether renewable biomass feedstock is available while not directly competing with the production of food. Farmers are one of the most important stakeholders in the biofuel supply chain and confront a range of uncertainties while entering the bioenergy market. Their decision-making process is extremely complex and rarely purely rational. Modeling farmer behavior requires considering a wide range of individual-level factors, socio-temporal dynamics, institutional settings, and their interactions. These characteristics make agent-based modeling a suitable framework for evaluating such systems. We developed a model to simulate farmer bioenergy crop adoption behavior across a 50-county study region in Nebraska, Kansas, and Colorado. The analysis considers adoption decisions for two bioenergy feedstocks, crop residues and energy crops. We examine the influence of individual and farm characteristics, market structure, social networks, and media influence on farmer adoption decisions. Our results indicate that different factors can have varied impacts on the speed of adoption for the crop residues and energy crops. Identifying levers that have the most impact on grower adoption can inform the design of interventions both from policy and private sector standpoints with important implications for the future the bioenergy industry.

09 BIOMASS FUELS↗

DOE OSTI2020

The role of nuclear in China’s energy future: insights from integrated assessment

China, the world’s largest electricity consumer, has strong motivations to deploy nuclear power due to increasing electricity demand and environmental concerns. However, there are social, institutional, and technical barriers to future nuclear expansion. This paper provides an updated assessment of nuclear energy potential in China with analyses at both national and provincial levels and compares results with studies previously conducted. Using an integrated assessment model, this paper considers the interactions among different socioeconomic development pathways, technology options, climate policies, and social/political concerns on inland siting. Among all factors explored, climate policies have the most significant impact on accelerating the deployment of nuclear technologies. Inland siting of nuclear power plants increases total capacity, but the impact is limited without climate policy. The amount of annual nuclear generation across scenarios and studies is unlikely to rise above 11% by 2030 and 30% by 2050 of total Chinese electricity generation. A dramatic increase in total Chinese nuclear energy generating capacity – around 3900 TWh of nuclear generation by 2050 – is only possible in scenarios where China sees electricity demand increase substantially, sticks to and tightens its current Paris Accord commitments, achieves low costs of nuclear technologies, and allows inland siting of nuclear power plants.

China, integrated assesment, Nuclear Power Plants↗

DOE OSTI2025

Cataloging US state policy patterns towards microgrid deployment

Frequent extreme weather events have called for rigorous and timely efforts for alternative non-wire solutions. These efforts are getting more widespread to offer a perfect alternative as the conventional grid becomes progressively less resilient. One of these solutions is microgrids that can disconnect from the grid and offer grid resilience during an outage. While this technology is still finding its footing in the industry, states across the US are employing policy patterns and forms of instruments to support its deployment. This study includes a systemic review of the US by conducting a binary analysis of all 50 states (including Washington D.C, excluding other US territories) using seven variables. The results show four major policy approaches to microgrids: i) supporting microgrids through a definitive legislative activity leading to further policy action; ii) direct efforts from the public utilities commissions without a concrete legislative push; iii) initiatives from institutions other than the commissions; and lastly, iv) self-initiated community and private consumer efforts. The results help understand what policy instruments are being used in each of these patterns to support this niche technology that still faces regulatory challenges.

Furqan, Maham↗

DOE OSTI2021

Decarbonizing via disparities: Problematizing the relationship between social identity and solar energy transitions in the United States

As solar adoption across the United States continues to grow, so do the gaps between rural and urban communities in how they choose to embrace these technologies, leading to serious questions of social justice and equity by researchers and policymakers alike. While recent studies have examined the racial and social justice elements of solar adoption alongside institutions' role in shaping pro-solar policies, codes, and code enforcement, an opportunity exists to discuss how the place and composition of the body politic in terms of race/ethnicity and rurality exists. This paper establishes a methodology for examining location and body politic composition concerning adopting all types of solar (residential, non-residential, utility-scale), utilizing the State of Georgia as a case study. Results indicate that the approach yields useful and informative findings; namely, there is a significant difference in adopting non-residential and utility-scale solar between rural and urban counties. We conclude by discussing further opportunities to expand on this analysis and the impact of assessing solar adoption in terms of value alignment between a body politic and the policies that shape the adoption of sustainable energy technologies. Finally, combining solar adoption information for the State of Georgia with Census data, this study compares solar adoption trends across counties--grouped by urban/rural classification and racial and ethnic majority.

14 SOLAR ENERGY↗

DOE OSTI2020

Challenges in the designing, planning and deployment of hydrogen refueling infrastructure for fuel cell electric vehicles

Hydrogen can power transportation with near zero greenhouse gas emissions. With government support, early market development is now underway in several nations thanks to technological advances in fuel cell vehicles and electricity generation from renewable energy. Deploying a sustainable hydrogen refueling infrastructure faces methodological and practical challenges ranging from the creation of appropriate codes to managing the co-evolution of the refueling network and growth of the stock of hydrogen fuel cell vehicles. Furthermore, this paper presents a comprehensive review of the challenges facing the designing, planning and deployment of hydrogen refueling infrastructure progress to date and outlook for the future. The design and costs of refueling infrastructure as well as the lifecycle environmental effects of hydrogen vehicles depend on how hydrogen is produced and delivered to refueling stations. In recent years, important advances have been made in methods for planning the numbers, sizes and location of hydrogen stations. Institutional barriers are also gradually being overcome. Co-evolving the deployment of stations and the demand for fuel cell vehicles remains a crucial subject for future research.

33 ADVANCED PROPULSION SYSTEMS↗