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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Comprehensive Evaluation of Agrivoltaics Research: Breadth, Depth, and Insights for Future Research

Agrivoltaics integrates agricultural production with solar energy generation to address challenges related to land use, food security, and renewable energy development. This study provides the most comprehensive evaluation to date of global agrivoltaic research, aiming to classify the literature, identify strengths and gaps, and guide future work. We systematically screened over 3000 English-language publications through 2023 for relevant agrivoltaic publications. A total of 670 studies were categorized in the InSPIRE Data Portal across five agrivoltaic activities and multiple hierarchical themes, including physical, biological, technological, social, and crosscutting domains. We found that research was concentrated on crop production, microclimate dynamics, and PV performance, with gaps in areas like human health, wildlife, policy, and standardized methodologies. Although the U.S. emphasizes animal grazing and habitat-based systems in practice, most U.S.-based studies focused disproportionately on crop production. The analysis revealed uneven geographic and topical representation and highlighted a lack of integrated, interdisciplinary approaches. This study concludes that while agrivoltaic research has grown rapidly, more coordinated efforts could support standardized data collection, address overlooked ecological and social impacts, and align research focus with real-world system implementation, ultimately improving the scalability and successful deployment of agrivoltaic systems.

14 SOLAR ENERGY↗
DOE OSTI2021

Integration of Open-Source URBANopt and Dragonfly Energy Modeling Capabilities into Practitioner Workflows for District-Scale Planning and Design

High-performance districts and communities offer opportunities for reducing energy use, emissions, and costs, and can be instrumental in helping cities achieve their climate goals. The design of such communities requires identification of opportunities early on and their re-evaluation throughout the planning process. There is a need for energy modeling tools that connect 3D Computer-Aided Design (CAD) platforms to simulation engines, enabling detailed energy analysis of districts within the workflows and tools used by practitioners. This paper introduces the Dragonfly and URBANoptTM combined toolset that supports the creation of urban models from a range of geometry formats typically used by designers and planners, and provides an integrated pathway to simulate district-scale energy systems. The toolset is piloted by a global architecture and master planning firm to evaluate several key urban-scale technical questions for the design of a district in Chicago. The findings indicate that, while energy savings can be achieved through traditional architectural studies and enhancements to individual building efficiency, the modeling toolset helps identify additional savings and insights that can be achieved when considering district-scale energy systems. Finally, this study demonstrates how the Dragonfly/URBANopt toolset can integrate with master planning workflows, thereby enabling an iterative performance-based design process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Hydropower operation in future power grid with various renewable power integration

Hydropower generation may play an increasingly important role in the power grid under increasing contribution of variable renewable sources such as wind and solar. An improved understanding of the changes to hydropower dispatch under future higher VRE grid conditions reveals research gap that should be informed power grid planning and reservoir water releases policies considering multiple other water uses and varying hydrologic condition. Here this study aims to understand the role of hydropower in a changing power grid by employing a production cost model, PLEXOS, across future power system scenarios, planning horizons, and regions. We explore optimized hydropower dispatch to understand its potential role in minimizing the system cost and renewable curtailment. We also examine the sensitivity of hydropower revenue under various grid scenarios of the Eastern U.S. and hydrology conditions. Results indicate hydropower generation follows net load and compensates for the variability of solar and wind generation. Although energy prices are lower during some periods in the future grid scenarios, there is a potential for higher revenue for hydropower by providing both energy and ancillary services during times of stress. Additionally, hydropower revenue is sensitive to hydrology in the SERC region, which we considered as an example. The feasibility of hydropower dispatching with higher ramps between low and high hourly-capacity factors, as indicated in the optimization model, requires further study to consider other water use and ecology constraints.

13 HYDRO ENERGY↗
DOE OSTI2025

Differential equations for cosmological correlators

Cosmological fluctuations retain a memory of the physics that generated them in their spatial correlations. The strength of correlations varies smoothly as a function of external kinematics, which is encoded in differential equations satisfied by cosmological correlation functions. In this work, we provide a broader perspective on the origin and structure of these differential equations. As a concrete example, we study conformally coupled scalar fields in a power-law cosmology. The wavefunction coefficients in this model have integral representations, with the integrands being the product of the corresponding flat-space results and “twist factors” that depend on the cosmological evolution. Similar twisted integrals arise for loop amplitudes in dimensional regularization, and their recent study has led to the discovery of rich mathematical structures and powerful new tools for computing multi-loop Feynman integrals in quantum field theory. The integrals of interest in cosmology are also part of a finite-dimensional basis of master integrals, which satisfy a system of first-order differential equations. We develop a formalism to derive these differential equations for arbitrary tree graphs. The results can be represented in graphical form by associating the singularities of the differential equations with a set of graph tubings. Upon differentiation, these tubings grow in a local and predictive fashion. In fact, a few remarkably simple rules allow us to predict — by hand — the equations for all tree graphs. While the rules of this “kinematic flow” are defined purely in terms of data on the boundary of the spacetime, they reflect the physics of bulk time evolution. We also study the analogous structures in tr ϕ 3 theory, and see some glimpses of hidden structure in the sum over planar graphs. This suggests that there is an autonomous combinatorial or geometric construction from which cosmological correlations, and the associated spacetime, emerge.

Cosmological models↗
DOE OSTI2025

Eocene-Oligocene Metamorphism, Fluid Flow and Deformation in the Ruby Mountains-East Humboldt Range Metamorphic Core Complex

Metamorphic core complexes are ubiquitous in collapsed orogens globally and play a primary role in crustal exhumation. Here, we investigate the metamorphic history of the Ruby Mountains-East Humboldt Range metamorphic core complex, Nevada, using petrochronology to understand how magmatism, metamorphism and deformation interact to modulate crustal rheology, and the timing of exhumation within the Sevier orogenic belt. Field study, microstructural analysis, thermobarometry and laser ablation split-stream monazite, titanite and allanite petrochronology of the mylonitic footwall were integrated to elucidate the pressure-temperature-time (P-T-t) evolution. Major-, trace-element and quartz-in-garnet thermobarometry show peak metamorphism occurred at 5.5–6 kbar and 600–650°C across the study area. Monazite and titanite U-(Th)-Pb petrochronology constrain this episode of metamorphism to 88–81 Ma with the structurally deepest samples yielding dates down to ca. 71 Ma. The preservation of peak metamorphic mineral assemblages indicates these rocks remained at near-peak temperature conditions into the Cenozoic. Cenozoic metamorphism occurred during a punctuated episode contemporaneous with the Great Basin ignimbrite flare up. All samples show a distinct 39–37 Ma population of monazite, titanite and allanite dates that correlate with the emplacement of quartz diorite and gabbro intrusions throughout the footwall. Accessory phases contain zoning textures in backscattered electron images that are consistent with fluid-mediated dissolution-reprecipitation reactions. The U-(Th)-Pb analyses from these zones yield 39–27 Ma dates interpreted as the timing of fluid flow. The results of this study elucidate the integrated importance of magmatism, melting and fluid flow in driving the coupled evolution of Late Cretaceous metamorphism within the Sevier hinterland and the subsequent Cenozoic metamorphic core complex development that exhumed the middle crust.

58 GEOSCIENCES↗
DOE OSTI2022

A polypeptide model for toxic aberrant proteins induced by aminoglycoside antibiotics

Aminoglycoside antibiotics interfere with the selection of cognate tRNAs during translation, resulting in the synthesis of aberrant proteins that are the ultimate cause of cell death. However, the toxic potential of aberrant proteins and how they avoid degradation by the cell’s protein quality control (QC) machinery are not understood. Here we report that levels of the heat shock (HS) transcription factor σ32 increased sharply following exposure of Escherichia coli to the aminoglycoside kanamycin (Kan), suggesting that at least some of the aberrant proteins synthesized in these cells were recognized as substrates by DnaK, a molecular chaperone that regulates the HS response, the major protein QC pathway in bacteria. To further investigate aberrant protein toxic potential and interaction with cell QC factors, we studied an acutely toxic 48-residue polypeptide (ARF48) that is encoded by an alternate reading frame in a plant cDNA. As occurred in cells exposed to Kan, σ32 levels were strongly elevated following ARF48 expression, suggesting that ARF48 was recognized as a substrate by DnaK. Paradoxically, an internal 10-residue region that was tightly bound by DnaK in vitro also was required for the ARF48 toxic effect. Despite the increased levels of σ32, levels of several HS proteins were unchanged following ARF48 expression, suggesting that the HS response had been aborted. Nucleoids were condensed and cell permeability increased rapidly following ARF48 expression, together suggesting that ARF48 disrupts DNA-membrane interactions that could be required for efficient gene expression. Our results are consistent with earlier studies showing that aberrant proteins induced by aminoglycoside antibiotics disrupt cell membrane integrity. Insights into the mechanism for this effect could be gained by further study of the ARF48 model system.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Optimizing metaproteomics database construction: lessons from a study of the vaginal microbiome

Metaproteomics, a method for untargeted, high-throughput identification of proteins in complex samples, provides functional information about microbial communities and can tie functions to specific taxa. Metaproteomics often generates less data than other omics techniques, but analytical workflows can be improved to increase usable data in metaproteomic outputs. Identification of peptides in the metaproteomic analysis is performed by comparing mass spectra of sample peptides to a reference database of protein sequences. Although these protein databases are an integral part of the metaproteomic analysis, few studies have explored how database composition impacts peptide identification. Here, we used cervicovaginal lavage (CVL) samples from a study of bacterial vaginosis (BV) to compare the performance of databases built using six different strategies. We evaluated broad versus sample-matched databases, as well as databases populated with proteins translated from metagenomic sequencing of the same samples versus sequences from public repositories. Smaller sample-matched databases performed significantly better, driven by the statistical constraints on large databases. Additionally, large databases attributed up to 34% of significant bacterial hits to taxa absent from the sample, as determined orthogonally by 16S rRNA gene sequencing. We also tested a set of hybrid databases which included bacterial proteins from NCBI RefSeq and translated bacterial genes from the samples. These hybrid databases had the best overall performance, identifying 1,068 unique human and 1,418 unique bacterial proteins, ~30% more than a database populated with proteins from typical vaginal bacteria and fungi. Our findings can help guide the optimal identification of proteins while maintaining statistical power for reaching biological conclusions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Understanding drivers of oil and gas well integrity issues in the greater wattenberg area of Colorado

Well integrity is critically important to maintain to minimize the environmental impacts of oil and gas development and other subsurface energy operations. The Wattenberg Field of Colorado—a top producing field with >40,000 wells—has one of the most robust publicly reported well integrity programs in the country. Here, in this study, we analyzed annular pressure and annular-fluid geochemical test results collected from Wattenberg wells through the end of 2019 to characterize the frequency and spatial variability of integrity issues in the field and understand their drivers. Estimated frequencies of integrity issues among tested wells were 8.2-17.1% between 1955 and 2019 and 6.1-11.4% in 2019 alone. The frequency of integrity issues was nearly four times greater in wells located above the Longmont Wrench Fault Zone. Potential drivers of integrity issues were identified using ensemble decision tree models trained with a broad set of relevant information. Models show that well integrity issues are spatially clustered on regional and sub-regional scales and suggest the relatively high frequency of integrity issues observed is likely attributed to geologic factors. These findings are valuable for regulatory agencies and operators seeking to inform well integrity monitoring, plugging, and emissions reduction efforts and design future subsurface energy projects.

03 NATURAL GAS↗
DOE OSTI2026

A comparative study of multimodal data fusion strategies for planetary spectroscopy

Integrating heterogeneous data sources can improve scientific inference when different modalities capture complementary information, but doing so is challenging in high-dimensional, small-sample settings. In spectroscopy for planetary exploration, Laser-Induced Breakdown Spectroscopy (LIBS), Raman Spectroscopy (Raman), Visible Infrared Spectroscopy (VISIR), and Mid-Infrared Spectroscopy (MIR) each examine different aspects of composition and mineralogy, raising fundamental questions about when and how data fusion improves predictive performance. Using a Mars-relevant set of geologic standards with measurements from all four modalities, we present a rigorous systematic evaluation of four data fusion strategies: low-level (data) fusion, mid-level (feature) fusion, high-level (decision) fusion, and residual-boosting (sequential) fusion. We assess performance in predicting oxide composition via nested cross-validation and corrected significance testing to evaluate whether data fusion improves upon single-modality baselines. We show that data fusion does not uniformly improve accuracy, and that observed gains are modest, oxide-dependent, and sensitive to modality and model structure. To move beyond aggregate accuracy metrics, we use model coefficients, permutation importance, and residual gain analysis to examine how the fusion models weight individual modalities and to identify patterns of apparent complementarity or redundancy. Though focused on spectroscopy for planetary exploration, our framework for data fusion evaluation and interpretation extends to other scientific domains with heterogeneous and scarce data and provides a principled approach evaluating data fusion strategies, interpreting modality contributions, and understanding tradeoffs among data fusion strategies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Cloud Process Coupling and Time Integration in the E3SM Atmosphere Model

Abstract In this study, we find significant sensitivity to the choice of time step for the Energy Exascale Earth System Model's atmospheric component, leading to large decreases in the magnitude of cloud forcing when the time step is reduced to 10 s. Reducing the time step size for the microphysics increases precipitation, leading to a drying of the atmosphere and an increase in surface evaporation. This effect is amplified when the microphysics is substepped together with other cloud physics processes. Coupling the model's dynamics and physics more frequently reduces cloud fraction at lower altitudes, while producing more cloud liquid at higher altitudes. Reducing the deep convection time step also reduces low cloud mass and cloud fraction. Together, these results suggest that cloud physics in a global circulation model can depend strongly on time step and, in particular, on the frequency with which cloud‐related processes are coupled with each other and with the model dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Business Environment Study (Subtask 5.1)

In 2016, WVR acquired the Wabash Integrated Gasification Combined Cycle (IGCC) Plant north of Terre Haute, Indiana. Initially, WVR intended to use the plant to produce ammonia using syngas converted to hydrogen. Part of the business plan was to capture and sequester the CO 2 byproduct with the goal of a net-zero carbon emitting plant. Now, with the demand for clean hydrogen-based power and fuel cell energy, the plant intends to produce power and sell hydrogen as a fuel source, still with the intent to sequester CO 2 and achieve net-zero emissions. The Wabash CarbonSAFE project’s objectives are to establish the feasibility of developing a commercial-scale geological storage complex at the WVR plant in Vigo County, Indiana, for storage of 50 million tonnes or more of CO 2 . The plant is expected to produce up to 2 million tons (1.82 million tonnes) of CO 2 annually as a byproduct of hydrogen production. Wabash CarbonSAFE has examined the feasibility of geologic storage of the CO 2 in the Potosi Dolomite Storage Complex of the Illinois Basin via an onsite characterization well at the WVR plant site. This document explores the business requirements to undertake such a project, outlining the outside influences on a business venture such as legislation, legal, regulatory, and business climate factors. This document then discusses the CO 2 source, potential partner sources, and the business financials that allow CCS to be commercially viable for Wabash Valley Resources.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Energy burden aware and thermal resilience informed thermal energy storage system planning for disadvantaged communities

Disadvantaged communities often face a disproportionate energy burden because they need to allocate a higher percentage of their income to energy costs. More importantly, climate change-induced extreme weather events, such as heat waves and severe cold snaps, exacerbate these communities’ energy burdens. As a result, low- and medium-income communities are more likely to experience energy supply disruptions, increased health risks, and elevated energy bills because of inadequate thermal insulation and airtightness in their houses. Thermal energy storage (TES) systems, such as large-scale (community-level) geothermal energy storage and small-scale (building-level) phase change material (PCM)–based storage, have a great potential to improve building energy efficiency and to enhance thermal comfort, load shifting, and integration with renewable energy. The objective of this study is to optimally allocate building level PCM-based TES systems at the community level by considering energy equity and extreme weather effects. To this end, we developed an energy burden and thermal resilience–informed TES system planning framework, which includes three modules: (1) a community-level energy burden and thermal resilience assessment module, (2) building-level a TES system integration and assessment module, and (3) a community-level optimal planning module. Case studies were conducted on four disadvantaged communities in Montgomery and Shelby Counties in Tennessee with energy burdens >10% and with high percentages of people of color. The results indicate that this comprehensive planning framework can assist disadvantaged communities in reducing their energy burden and in bolstering their resilience against the adverse effects of climate change.

Shen, Zhenglai↗
DOE OSTI2025

Status of the FCC-ee interaction region design

This paper presents a comprehensive overview of the Machine Detector Interface (MDI) design developed for the FCC-ee Feasibility Study. It highlights novel studies related to the lightweight interaction region, including a mechanical model of the vacuum chambers, integration of the vertex detector, the MDI alignment system, and assessments of machine-induced backgrounds. The small beam pipe radius and thickness, as well as the high power to be dissipated, require state-of-the-art mechanical design. The integration of all mechanical elements and detectors is challenging, necessitating careful studies to allow fulfilling conflicting requirements. The optimisation of the machine detector interface against formidable backgrounds is presented.

Beam-induced backgrounds↗
DOE OSTI2025

Evaluation of normalization strategies for mass spectrometry-based multi-omics datasets

Introduction Data normalization is crucial for multi-omics integration, reducing systematic errors and maximizing the likelihood of discovering true biological variation. Most studies assess normalization for a single omics type or use datasets from separate experiments. Few address time-course data, where normalization might bias temporal differentiation. In this study, we compared common normalization methods and a machine learning approach, Systematical Error Removal using Random Forest (SERRF), using multi-omics datasets generated from the same experiment—even from the same cell lysate. Objectives To develop a straightforward process to assess normalization effects and identify the most robust methods across multi-omics datasets. Methods We analyzed metabolomics, lipidomics, and proteomics datasets from primary human cardiomyocytes and motor neurons exposed to acetylcholine-active compounds over time. Normalization effectiveness was evaluated based on improvement in QC features consistency and observing the change in treatment and time-related variance. Results Probabilistic Quotient Normalization (PQN) and Locally Estimated Scatterplot Smoothing (LOESS) QC were identified as optimal for metabolomics and lipidomics, while PQN, Median, and LOESS normalization excelled for proteomics. These methods consistently enhanced QC feature consistency in metabolomics and lipidomics, and preserved time-related variance or treatment-related variance in proteomics, demonstrating their effectiveness and robustness. SERRF normalization, applied only to metabolomics in this study, outperformed other methods in some datasets but inadvertently masked treatment-related variance in others. Conclusion Our evaluation identified PQN and LoessQC as the top methods for metabolomics and lipidomics, and PQN, Median, and Loess normalization for proteomics, in multi-omics integration in a temporal study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Effective Kitchen Ventilation for Healthy Zero Net Energy Homes with Natural Gas

Past studies indicate that kitchen ventilation that minimally complies with California’s Residential Building Code is inadequate at controlling combustion pollutants from natural gas burners and particulate matter produced during cooking. Effectiveness is further limited by misperceptions that kitchen ventilation is infrequently needed. This project developed the technical basis for updating kitchen ventilation requirements to protect health in new California homes, especially in smaller homes common among low-income renters. Tasks included (1) a field study of ventilation equipment performance and indoor air quality in 23 low-income apartments at four sites; (2) analysis of range hood use related to cooking time and household parameters using data from 54 houses and 17 low-income apartments; (3)a measurement-based study to quantify performance of over-the-range microwave ovens with integrated exhaust fans;and (4) pollutant exposure simulations to inform capture efficiency standards.The field study found operational deficiencies with mechanical ventilation systems in a substantial fraction of low-income apartments that affected performance, resulting in higher exposures to pollutants generated indoors. Using gas cooking burners produced high short-term and weekly time-averaged nitrogen dioxide in apartments.Range hoods were used more frequently with cooking in houses (36percent) than apartments (28percent); use increased with overall cooking frequency in a home and with duration of cooktop but not oven events; actual use was correlated to, but lower than,self-reported use;and use was more frequent in houses when cooking generated any fine particulate matter (PM2.5)or when high PM2.5resulted from cooking in apartments. Performance of over-the-range microwaves with integrated exhaust fans was similar to that of range hoods of comparable price. Simulation analysis found that performance standards need to be updated to ensure that kitchen exhaust ventilation adequately protects for substantial cooking in new California residences.

03 NATURAL GAS↗
DOE OSTI2021

Toward Urban Water Security: Broadening the Use of Machine Learning Methods for Mitigating Urban Water Hazards

Due to the complex interactions of human activity and the hydrological cycle, achieving urban water security requires comprehensive planning processes that address urban water hazards using a holistic approach. However, the effective implementation of such an approach requires the collection and curation of large amounts of disparate data, and reliable methods for modeling processes that may be co-evolutionary yet traditionally represented in non-integrable ways. In recent decades, many hydrological studies have utilized advanced machine learning and information technologies to approximate and predict physical processes, yet none have synthesized these methods into a comprehensive urban water security plan. In this paper, we review ways in which advanced machine learning techniques have been applied to specific aspects of the hydrological cycle and discuss their potential applications for addressing challenges in mitigating multiple water hazards over urban areas. We also describe a vision that integrates these machine learning applications into a comprehensive watershed-to-community planning workflow for smart-cities management of urban water resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Performance evaluation of underground thermal storage integrated dual-source heat pump systems

The increasing demand for electricity stresses the existing electric grids. Buildings consume 73% of all U.S. electricity and are responsible for 30% of U.S. greenhouse gas emissions. Integrating thermal energy storage (TES) in building heating/cooling systems, which consume considerable electricity, can mitigate the challenges to electric grids. Here, this study reports on a novel thermal energy storage device integrated heat pump system to reshape the building electricity demand profile while maintaining thermal comfort. The annual performance of the proposed system has been evaluated through a dynamic system simulation with high fidelity in the Modelica platform. The dynamic model of the novel hybrid component named ‘dual purpose underground thermal battery’ was developed and validated. It was then incorporated into the system model. Given a time-of-use tariff, a rule-based control strategy was designed to shift the electric demand and switch the heat pump source for a typical single-family house in different climate zones of the United States. The system performance of the new TES-integrated dual-source heat pump was compared with that of a conventional air-source heat pump system. The results indicate that the proposed system can reduce the annual HVAC electricity cost by up to 52% while saving 45.2% on electricity consumption. In the Northern areas, the annual peak load of the HVAC system can be reduced by 64.9%. However, this reduction is less in the Southern areas as the system’s higher efficiency in winter dominates the overall energy-saving potential.

25 ENERGY STORAGE↗