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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Quarterly Research Performance Progress Report (Q8)

As part of Task 1, we have started by testing our modeling capabilities by reproducing isothermal DFIT simulations presented in the literature. Once satisfied with the results we have started by targeting the modeling of the DFITs at conducted at well 58-32. We have a identified a specific test (cycle 4 in zone 2) as the most interesting to be model with GEOS hydraulic fracturing module. Thus, we have first produced results with an isothermal model and adjusted model parameters to get a satisfying match with field pressure data. The, we have added thermal effects and compared the modeling results with and without thermal effects to estimate how thermal effects may influence test interpretation. Models seem to suggest that, for small volumes of fluid, thermal effects are moderate. In Task 2, we have adapted GEOS phase-field formulation to be able to simulate near-wellbore hydraulic fracture nucleation and propagation. We have devised a novel formulation that, compared to other existing ones, incorporates rock strengths. We have submitted a journal publication about our work. We are currently employing this phase-field formulation to model the experiments taking place at U Pitt and help us understand the effect of various parameters. In Task 3, we have built a model of the region surround well 16A and have started modeling stage 3 stimulation because of its simpler planar geometry. After calibrating simulation parameters using known analytical solutions, we have simulated the stage 3 stimulation using our isothermal hydraulic fracturing module, varying the permeability field, the stress conditions including different physics to get a better understanding of the numerical challenges and of the effects of varying these parameters on the simulation results. In Task 4 laboratory experimentation, a set of specialized drilling and injection tools has been customized and constructed to accommodate an inclined well with an orientation of up to 30 degrees relative to material anisotropy or principal stress axes. These inclined samples have also undergone thermal stress and hydraulic fracturing at a temperature of 190 degrees Celsius. Furthermore, both vertical and deviated sampling testing setups enable an extended analysis of post-peak pressure behaviors, facilitating post-test pressure analyses such as the G-function, step rate, and fracture reopening measurements. Thus, the key components of in-situ stress estimation can be extracted and validated through our experiment, providing a solid foundation for validating existing in-situ stress estimation theories or proposing new ones. Simultaneously, we are integrating computer vision techniques with traditional experimental fracture observation methods such as multi-overcore/slicing and water-penetration fracture observation. This combination will prove beneficial in populating the hydraulic fracture patterns database, generated under challenging EGS conditions. This approach aims to deepen our understanding of the complexities in EGS reservoirs and pave the way for future data-driven investigations. Additionally, PITT has also equipped the ELE International compression machine, which is now prepared for conducting indirect tensile and fracture toughness tests. These tests will aid in characterizing how rock fabrics influence the resulting fracture patterns. Additionally, we have completed the required personnel training and gained access to Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS) for conducting more detailed characterization and analysis of rock fabrics, as well as the examination of thermal and hydraulically induced fracture patterns. Thus, the PITT team has effectively demonstrated the capabilities of our experimental apparatuses in exploring the thermal effects, well deviation angles, material anisotropy, and operational choices (such as circulation rate, injection fluid viscosity, and injection rate) and their impact on pressure responses and fracture trajectories under the Utah FORGE conditions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Detecting technological maturity from bibliometric patterns

We report the capability to identify emergent technologies based upon easily accessed open-source indicators, such as publications, is important for decision-makers in industry and government. The scientific contribution of this work is the proposition of a machine learning approach to the detection of the maturity of emerging technologies based on publication counts. Time-series of publication counts have universal features that distinguish emerging and growing technologies. We train an artificial neural network classifier, a supervised machine learning algorithm, upon these features to predict the maturity (emergent vs. growth) of an arbitrary technology. With a training set comprised of 22 technologies we obtain a classification accuracy ranging from 58.3% to 100% with an average accuracy of 84.6% for six test technologies. To enhance classifier performance, we augmented the training corpus with synthetic time-series technology life cycle curves, formed by calculating weighted averages of curves in the original training set. Training the classifier on the synthetic data set resulted in improved accuracy, ranging from 83.3% to 100% with an average accuracy of 90.4% for the test technologies. The performance of our classifier exceeds that of competing machine learning approaches in the literature, which report an average classification accuracy of only 85.7% at maximum. Moreover, in contrast to current methods our approach does not require subject matter expertise to generate training labels, and it can be automated and scaled.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Title Coherent X-ray Studies of Surface Growth and Patterning Processes

X-ray Photon Correlation Spectroscopy (XPCS) is being developed as a tool to study nanoscale dynamics of fluctuations during thin film growth and surface patterning. XPCS examines the evolution of the X-ray scattering speckle pattern in reciprocal space to reveal dynamics information not accessible through any other means. Unlike low-coherence conventional X-ray scattering, which incoherently averages over different regions of a sample, coherent X-ray scattering is sensitive to the detailed structure of a given sample at that moment in time. In thin film growth processes, heterodyning, which occurs due to coherent mixing of two scattered signals, can be used to investigate the relationship between surface growth velocity and defect propagation. And, for polycrystalline thin film growth, the spatial coherence of the X-ray beam can substitute for the missing spatial coherence of the growth process to track layered growth in detail, even in a growth regime in which there are no conventional growth oscillations of the X-ray intensity. This has opened the door for detailed dynamics studies of individual atomic layers during real-world growth and patterning, not just in perfect single-crystal growth cases, which greatly expands the applicability of in-situ X-ray scattering methods. Step-flow dynamics in mounded polycrystalline growth has been studied separately for two thin film organic semiconductors deposited by thermal deposition in a vacuum environment, C60 and diindenoperylene (DIP). Highly oriented polycrystalline thin films are readily obtained in both systems, where mounds are composed of crystalline monolayer-height steps and terraces in a so-called wedding cake morphology. The formation of mounds is understood to be due to significant Ehrlich-Schwoebel step edge barriers that inhibit molecules from hopping down from one layer to the one below. The mounds exhibit local step flow, which can be monitored using coherent X-ray scattering. This is made possible due to heterodyning between scattering from the average mounds and the moving steps, which becomes visible in XPCS analysis. The effect of desorption, i.e. re-evaporation of deposited molecules is found to be important for understanding these processes. The impact of this work is to enable testing of models of step dynamics, the shape of mounds, and merging of mounds to form continuous thin films. Highly ordered polycrystalline thin films deposited on inexpensive substrates have applications in thin film solar cells and other organic electronic devices. In a separate set of experiments, speckle analysis during self-organized ion beam nanopatterning reveals memory stretching back to the beginning of patterning in the early stages and enables measurement of the velocity of self-organized patterns across surfaces providing the possibility of stringent new tests of the theory of pattern formation and motion.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Mixed Length Scale Model for Migrating Fluvial Bedforms

With the expansion of hydropower, in-stream converters, flood-protection infrastructures, and growing concerns on deltas fragile ecosystems, there is a pressing need to evaluate and monitor bedform sediment mass flux. It is critical to estimate real-time bedform size and migration velocity and provide a theoretical framework to convert easily accessible time histories of bed elevations into spatially evolving patterns. In this study, we collected spatiotemporally resolved bathymetries from laboratory flumes and the Colorado River in statistically steady, homogeneous, subcritical flow conditions. Wave number and frequency spectra of bed elevations show compelling evidence of scale-dependent velocity for the hierarchy of migrating bedforms observed in the laboratory and field. New scaling laws were applied to describe the full range of migration velocities as function of two dimensionless groups based on the bed shear velocity, sediment diameter, and water depth. Further simplification resulted in a mixed length scale model estimating scale-dependent migration velocities, without requiring bedform classification or identification.

58 GEOSCIENCES↗
DOE OSTI2024

Explaining Health Risk Behaviors in the U.S. with Social Deprivation at Local and Regional Levels

Health risk behaviors are precursors to many chronic health outcomes, and hence, they pose a challenge to public health. Social deprivation undoubtedly creates circumstances that limit access to healthy habits. Moreover, broad regional effects (weather patterns, political ideology, social norms), and local characteristics (cultural notions and barriers, urban places) also influence lifestyle choices and must be accounted for to truly understand the impact of social deprivation on risky behaviors. This research fills the knowledge gap in epidemiological modeling of health risk behaviors by leveraging machine learning to find associations between social deprivation and health risk behaviors, when adjusted by regional and local effects. Four health risk behaviors, namely, binge drinking, smoking, lack of sleep, and lack of physical activity from the CDC PLACES project are considered in a single framework to understand and compare the interplay between local/regional characteristics and seven measures of social deprivation. Our results indicate that local and/or regional factors rise to the top for three out of four risk behaviors (binge drinking, smoking and lack of sleep) out-competing social deprivation measures. Un-entangling the geographical effects reveals that poverty, educational attainment and non-employment are the three deprivation measures most significantly associated with all four health risk factors. The research thus indicates that public health policies to promote healthy lifestyle behaviors must seek to remedy social deprivation, but using socially and culturally sensitive interventions.

Gokhale, Swapna↗
DOE OSTI2024

Streamflow measurements from four sites on the Tuolumne River in Yosemite National Park from Water Years 2002 to 2021

Regions with remote and complex terrain experience spatially varying streamflow patterns, but are often poorly sampled due to difficult access. This data package includes streamflow measurements collected using low-visibility and low-impact installations at four sites on the Tuolumne River in Yosemite National Park, for water years 2002 to 2021. The resulting data set offers a unique opportunity to explore hydrologic processes in complex terrain.This data package contains half-hourly recordings of unvented pressure, vented pressure, and water temperature are measured and used to estimate discharge and stage height. Discharge flags provide insight into data anomalies. This dataset is formatted in accordance with ESS-Dive's Hydrologic Monitoring and File Level Metadata Formats. It contains the following files:1) Folder containing four csv files of time series streamflow measurements (unvented pressure, vented pressure, estimated discharge, water temperature, stage height, and discharge flag) from four locations on the Tuolumne River2) Data dictionary (dd.csv) containing units, definitions, human readable column names, and data type for all column headers throughout the dataset3) File-level metadata (FLMD.csv) containing metadata for files contained in the dataset4) Installation methods (InstallationMethods.csv) containing metadata on sensor installation

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

PPI DataHub Project Data Package: S. elongatus PCC 7942 Circadian Control Bioproduction Metabolomics (PB-DP5)

The purpose of this experiment was to evaluate how circadian clock regulation impacts carbon partitioning between storage, growth, and product synthesis in Synechococcus elongatus PCC 7942 in providing insights to strategies for enhanced bioproduction. Culture samples were collected at 0, 0.5, 1, 2, 4, 6, and 8 hours for extracellular sucrose analysis. Circadian metabolomics data was acquired using a Agilent single quadrupole gas chromatography-mass spectrometer and processed using Agilent Mass Hunter for targeted sucrose quantification. Metabolomic analysis of PCC 7942 light-dark cycle cultures transitioned to constant light revealed distinct temporal patterns in sucrose production. Processed metabolomic datasets are openly accessible from the PNNL DataHub project dataset download page and contain secondary processed GC-MS results files and supporting metadata materials linked to relevant source code information supporting data transparency and reuse.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Increasing the Scale of the Mass Spectrometry Query Language Compendium with Explainable AI

A significant bottleneck in metabolomics data interpretation is the effective use of domain knowledge to assign structural information based on fragmentation patterns. The mass spectrometry query language (MassQL) aims to make this process accessible and applicable across multiple analysis platforms. While advanced computational methods are capable of predicting compound structures from fragmentation data, AI/ML approaches often rely on complex, opaque criteria that are difficult to interpret or modify. As a result, their predictive patterns cannot be readily translated into human-readable rules, such as those used in MassQL. Here, in this study, we introduce ChemEcho, a machine learning embedding method that converts tandem mass spectrometry data into sparse feature vectors containing peak and neutral mass subformulae to enhance explainable AI/ML-based methods. An advantage of this approach is that decision trees trained using these feature vectors can be directly translated to MassQL. Using a battery of decision trees trained using ChemEcho embeddings to predict molecular attributes, we generated over 1500 MassQL queries for 765 molecular features and evaluated their precision and recall. From these queries, the 50 highest-performing queries were integrated into the MassQL compendium. This set of generated MassQL queries included environmentally and biologically relevant classes such as PFAS and molecules containing phosphate or sulfate substructures. To illustrate the impact these queries would have on a typical metabolomics experiment, these MassQL queries were applied to a public metabolomics data set─resulting in a marked increase in the structural information derived from tandem mass spectra. Access and reuse of these queries is expected to enhance structural annotation in untargeted experiments, leading to more specific claims and advancing many applications in metabolomics.

Harwood, Thomas V. [USDOE Joint Genome Institute (↗
DOE OSTI2022

Plant Nutrition Influences Resistant Maize Defense Responses to the Fall Armyworm ( Spodoptera frugiperda )

Plants are often confronted by different groups of herbivores, which threaten their growth and reproduction. However, they are capable of mounting defenses against would-be attackers which may be heightened upon attack. Resistance to insects often varies among plant species, with different genotypes exhibiting unique patterns of chemical and physical defenses. Within this framework, plant access to nutrients may be critical for maximal functioning of resistance mechanisms and are likely to differ among plant genotypes. In this study, we aimed to test the hypothesis that access to nutrition would alter the expression of plant resistance to insects and alter insect performance in a manner consistent with fertilization regime. We used two maize (Zea mays) genotypes possessing different levels of resistance and the fall armyworm (Spodoptera frugiperda) as model systems. Plants were subjected to three fertilization regimes prior to assessing insect-mediated responses. Upon reaching V4 stage, maize plants were separated into two groups, one of which was infested with fall armyworm larvae to induce plant defenses. Plant tissue was collected and used in insect bioassays and to measure the expression of defense-related genes and proteins. Insect performance differed between the two plant genotypes substantially. For each genotype, fertilization altered larval performance, where lower fertilization rates hindered larval growth. Induction of plant defenses by prior herbivory substantially reduced naïve fall armyworm growth in both genotypes. The effects between fertilization and induced defenses were complex, with low fertilization reducing induced defenses in the resistant maize. Gene and protein expression patterns differed between the genotypes, with herbivory often increasing expression, but differing between fertilization levels. The soluble protein concentrations did not change across fertilization levels but was higher in the susceptible maize genotype. These results demonstrate the malleability of plant defenses and the cascading effects of plant nutrition on insect herbivory.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Survey on Efficient and Productive Use of Electricity In Women-Run Small Businesses in Uganda

In Uganda, women make up a large portion of the service sector, notably in informal small and micro businesses such as retail shops, food preparation, tailoring, sewing, beer brewing, basket weaving, healthcare, and hairdressing. Lawrence Berkeley National Laboratory (LBNL), and USAID, in partnership with the Clean Energy Enthusiasts (CEE), a local implementer in Uganda, designed and conducted a participatory survey to collect baseline data and information on the current state of benefits to energy access. The study included data on the uptake of efficient and productive electric (EPUE) equipment, business skills, and financial needs among small and mid-size women-led businesses in Uganda. The objective of the survey was to build evidence and identify economic activities where access to electricity has a positive impact on women’s empowerment by helping them develop new and existing businesses, improve productivity, and increase their income. The survey included questions about the type of electric equipment used and needed, electric consumption patterns, alternative sources to electricity, and business and capital barriers related to increased access. The survey results provided the basis for designing a training program tailored to the need of women entrepreneurs in the region.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Imaging conical intersection dynamics during azobenzene photoisomerization by ultrafast X-ray diffraction

Significance Vibronic coherences are unique features that emerge in the decisive moments of photochemistry and photophysics. Here we demonstrate how X-ray diffraction can access fundamental information about these coherences. This is enabled by recent developments at free-electron lasers, working toward temporal resolution and single-molecule accessibility of scattering-based measurements. Time-resolved diffraction patterns of the isomerization of azobenzene are simulated. The process is monitored in time via the momentum-space signal, with a special focus on the mixed elastic/inelastic scattering from coherences. We give practical ideas on how this relatively weak contribution to the signal can potentially be retrieved. A direct connection to the real-space movie of the conical intersection dynamics is made, enabling the observation of quantum coherences that direct chemical processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Exploring Nonmotorized Travel in New York State Using 2017 National Household Travel Survey Data

This report presents systematic analysis of nonmotorized travel behavior within New York State (NYS) utilizing 2017 National Household Travel Survey data. As walking and biking assume increasingly prominent roles in advancing active transportation objectives, accessible mobility, and sustainable transportation systems, comprehensive understanding of these modal patterns becomes essential for evidence-based policy development and strategic planning initiatives. Recognizing the substantial geographic, demographic, and socioeconomic heterogeneity characterizing NYS—spanning from the concentrated urban fabric of New York City (NYC) to dispersed suburban and rural contexts—this analysis employs the structured "4Ws" analytical framework to examine participant demographics, spatial and temporal distributions, and motivational factors underlying active transportation choices relative to motorized alternatives. This methodological approach captures modal behavior patterns, user characteristics, trip purposes, and temporal variations across the state's diverse contexts. Additionally, the research examines behavioral differences among distinct user classifications, including walk-only and bike-only travelers, while conducting comparative analysis of nonmotorized travel patterns between ALICE (Asset Limited, Income Constrained, Employed) and non-ALICE household categories.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Results From Invoking Artificial Neural Networks to Measure Insider Threat Detection & Mitigation

Advances on differentiating between malicious intent and natural “organizational evolution” to explain observed anomalies in operational workplace patterns suggest benefit from evaluating collective behaviors observed in the facilities to improve insider threat detection and mitigation (ITDM). Advances in artificial neural networks (ANN) provide more robust pathways for capturing, analyzing, and collating disparate data signals into quantitative descriptions of operational workplace patterns. In response, a joint study by Sandia National Laboratories and the University of Texas at Austin explored the effectiveness of commercial artificial neural network (ANN) software to improve ITDM. Overall, this research demonstrates the benefit of learning patterns of organizational behaviors, detecting off-normal (or anomalous) deviations from these patterns, and alerting when certain types, frequencies, or quantities of deviations emerge for improving ITDM. Evaluating nearly 33,000 access control data points and over 1,600 intrusion sensor data points collected over a nearly twelve-month period, this study's results demonstrated the ANN could recognize operational patterns at the Nuclear Engineering Teaching Laboratory (NETL) and detect off-normal behaviors—suggesting that ANNs can be used to support a data-analytic approach to ITDM. Several representative experiments were conducted to further evaluate these conclusions, with the resultant insights supporting collective behavior-based analytical approaches to quantitatively describe insider threat detection and mitigation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

Dual-Wavelength Simultaneous Patterning of Degradable Thermoset Supports for One-Pot Embedded 3D Printing

Vat photopolymerization (VP) techniques have enabled the fabrication of complex geometries while balancing high precision and fast processing times. 3D printed objects are traditionally built layer-by-layer with newly cured layers being structurally supported by previous ones. Fabricating unsupported features such as overhangs and arches risks misalignment and sagging, limiting the range of accessible designs. To overcome this issue, support structures are fabricated along with the primary object as temporary scaffolds that provide stability and conserve print fidelity. For VP specifically, patterning dissolvable sacrificial supports is attractive to avoid manual removal after printing. In this study, we demonstrate a base-degradable thermoset to pattern print supports in a one-pot formulation along with the primary structural material. Efficient printing is enabled using a dual-wavelength negative imaging (DWNI) DLP printer that patterns the degradable thermoset with visible light and the permanent network with UV light, which are simultaneously projected using a single digital micromirror device (DMD). Printed objects undergo thermal postprocessing to enhance the final conversion of the primary material, after which thermoset supports are degraded in a basic, aqueous solution. This approach provides a robust method for the dual-wavelength patterning of sacrificial thermoset supports, broadening the range of accessible 3D printable materials and geometries.

3D printing↗
DOE OSTI2025

Hourly Load Profile Dataset for Electric Port Cargo Handling Equipment in the United States

Historically, ports have relied on fossil fuels, particularly diesel, as their primary energy source. Transitioning to electric cargo handling equipment (eCHE) offers a promising solution, as this relatively mature technology eliminates tailpipe emissions, reduces harmful airborne particulates, lowers noise pollution, and supports decarbonization. This study develops an initial estimation of hourly electricity demand for eCHE at the top 25 container ports (by tonnage) in the United States. These datasets, accessible at data.nrel.gov/submissions/281, provide valuable insights into the electricity demand patterns and potential grid impacts associated with widespread eCHE adoption, forming a foundation for future refinement based on stakeholder feedback.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Competitive Exclusion and Metabolic Dependency among Microorganisms Structure the Cellulose Economy of an Agricultural Soil

Microorganisms that degrade cellulose utilize extracellular reactions that yield free by-products which can promote interactions with noncellulolytic organisms. We hypothesized that these interactions determine the ecological and physiological traits governing the fate of cellulosic carbon (C) in soil. We performed comparative genomics with genome bins from a shotgun metagenomic-stable isotope probing experiment to characterize the attributes of cellulolytic and noncellulolytic taxa accessing 13 C from cellulose. We hypothesized that cellulolytic taxa would exhibit competitive traits that limit access, while noncellulolytic taxa would display greater metabolic dependency, such as signatures of adaptive gene loss. We tested our hypotheses by evaluating genomic traits indicative of competitive exclusion or metabolic dependency, such as antibiotic production, growth rate, surface attachment, biomass degrading potential, and auxotrophy. The most 13 C-enriched taxa were cellulolytic Cellvibrio (Gammaproteobacteria) and Chaetomium (Ascomycota), which exhibited a strategy of self-sufficiency (prototrophy), rapid growth, and competitive exclusion via antibiotic production. Auxotrophy was more prevalent in cellulolytic Actinobacteria than in cellulolytic Proteobacteria, demonstrating differences in dependency among cellulose degraders. Noncellulolytic taxa that accessed 13 C from cellulose (Planctomycetales, Verrucomicrobia, and Vampirovibrionales) were also more dependent, as indicated by patterns of auxotrophy and 13 C labeling (i.e., partial labeling or labeling at later stages). Major 13 C-labeled cellulolytic microbes (e.g., Sorangium, Actinomycetales, Rhizobiales, and Caulobacteraceae) possessed adaptations for surface colonization (e.g., gliding motility, hyphae, attachment structures) signifying the importance of surface ecology in decomposing particulate organic matter. Our results demonstrated that access to cellulosic C was accompanied by ecological trade-offs characterized by differing degrees of metabolic dependency and competitive exclusion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Policy and Regulatory Environment for Utility-Scale Energy Storage: Bangladesh

Bangladesh has experienced significant economic growth and poverty reduction over the past several decades. Recognizing the central role electricity plays in economic development, the Government of Bangladesh (GOB) has established policies to accelerate the growth of the electric power sector. The Bangladesh power grid is transforming into one marked by declining reliance on domestic natural gas reserves and oil-based rental power plants, increasing renewable energy contribution, and shifting demand patterns. The GOB is now reconsidering its prior plans to increase the share of coal capacity in the generation mix to meet demand, shifting its focus instead to electricity imports from neighboring countries, nuclear generation, liquified natural gas imports, and domestic renewable resources such as wind and solar. However, investments in the transmission and distribution system, as well as ancillary services, have not kept pace with investments in generation resources over the past decade. Thus, Bangladesh electricity consumers still experience outages and poor power quality despite adequate installed capacity. On the demand side, population growth and industrialization have fueled steady growth in electricity consumption as efforts to expand access to electricity enabled near-universal electricity access by mid-2020. The combined changes in the mix of generation resources and patterns of electricity demand present new challenges and opportunities in operating and maintaining a reliable power system. Energy storage has the potential to help meet these challenges and accelerate Bangladesh’s energy transition. Declining costs for some energy storage technologies make them increasingly cost-effective solutions to provide a wide range of grid services. Previous analyses of energy storage in the region have identified several potential applications for storage at the bulk system level, including energy arbitrage, ancillary services, and transmission network support. The potential for storage to meet these needs depends on many factors, including physical characteristics of the power system and the policy and regulatory environments in which these energy storage assets would operate. This report applies an Energy Storage Readiness Assessment the National Renewable Energy Laboratory developed for policy makers and regulators to identify priority areas of focus as they continue to develop the appropriate suite of policies, programs, and regulations to enable storage deployment. This assessment uses a simple evaluation scheme to identify the barriers and opportunities for utility-scale energy storage within Bangladesh’s policy and regulatory environment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Influence of Geography on Prostate Cancer Treatment

Several definitive treatment options are available for prostate cancer, but geographic access to those options is not uniform. We created maps illustrating provider practice patterns relation to patients and assessed the influence of distance to treatment receipt.

62 RADIOLOGY AND NUCLEAR MEDICINE↗