Search NASA⌕ Search

SEARCH · Search NASA

Results for “FAIR”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Dark scalars and heavy neutral leptons at DarkQuest

The proposed DarkQuest beam dump experiment, a modest upgrade to the existing SeaQuest/SpinQuest experiment, has great potential for uncovering new physics within a dark sector. We explore both the near-term and long-term prospects for observing two distinct, highly-motivated hidden sector benchmark models: heavy neutral leptons and Higgs-mixed scalars. We comprehensively examine the particle production and detector acceptance at DarkQuest, including an updated treatment of meson production, and light scalar production through both bremsstrahlung and gluon-gluon fusion. In both benchmark models, DarkQuest will provide an opportunity to probe previously inaccessible interesting regions of parameter space on a fairly short timescale when compared to other proposed experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Color-octet scalars in Dirac gaugino models with broken R symmetry

In this work we study the collider phenomenology of color-octet scalars ( sgluons ) in supersymmetric models with Dirac gaugino masses that feature an explicitly broken R symmetry ( R - broken models ). We construct such models by augmenting minimal R -symmetric models with a fairly general set of supersymmetric and softly supersymmetry-breaking operators that explicitly break R symmetry. We then compute the rates of all significant two-body decays and highlight new features that appear as a result of R symmetry breaking, including enhancements to extant decay rates, novel tree- and loop-level decays, and improved cross sections of single sgluon production. We demonstrate in some detail how the familiar results from minimal R -symmetric models can be obtained by restoring R symmetry. In parallel to this discussion, we explore constraints on these models from the Large Hadron Collider. We find that, in general, R symmetry breaking quantitatively affects existing limits on color-octet scalars, perhaps closing loopholes for light CP-odd (pseudoscalar) sgluons while opening one for a light CP-even (scalar) particle. Qualitatively, however, we find that — much as for minimal R -symmetric models, despite stark differences in phenomenology — scenarios with broken R symmetry and two sgluons below the TeV scale can be accommodated by existing searches.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A defect in AdS 3 /CFT 2 duality

AdS 3 string theory in the stringy regime k = (R AdS /ℓ s ) 2 < 1 provides a laboratory for the study of holography in which both sides of AdS/CFT duality are under fairly good control. Worldsheet string theory is solvable, and for closed strings the dual spacetime CFT is a deformation of a symmetric product orbifold. Here we extend this construction to include open strings by adding a probe D-string, described semiclassically by an AdS 2 D-brane in AdS 3 . The dual defect or boundary conformal field theory (BCFT) is again a deformed symmetric product, which now describes the Fock space of long open and closed strings near the AdS boundary, with a boundary deformation implementing the open/closed transition in addition to the symmetric product $\mathbb{Z}$ 2 twist deformation that implements closed string joining/splitting. The construction thus provides an explicit example of an AdS 3 /BCFT 2 duality.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Distinctive signals of frustrated dark matter

We study a renormalizable model of Dirac fermion dark matter (DM) that communicates with the Standard Model (SM) through a pair of mediators — one scalar, one fermion — in the representation (6, 1, $\frac{4}{3}$) of the SM gauge group SU(3) c x SU(2) L x U(1) Y . While such assignments preclude direct coupling of the dark matter to the Standard Model at tree level, we examine the many effective operators generated at one-loop order when the mediators are heavy, and find that they are often phenomenologically relevant. We reinterpret dijet and pair-produced resonance and jets + E$^{miss}_{T}$ searches at the Large Hadron Collider (LHC) in order to constrain the mediator sector, and we examine an array of DM constraints ranging from the observed relic density Ω χ h$^{2}_{Planck}$ to indirect and direct searches for dark matter. Tree-level annihilation, available for DM masses starting at the TeV scale, is required in order to produce Ω χ h$^{2}_{Planck}$ through freeze-out, but loops — led by the dimension-five DM magnetic dipole moment — are nonetheless able to produce signals large enough to be constrained, particularly by the XENON1T experiment. In some benchmarks, we find a fair amount of parameter space left open by experiment and compatible with freeze-out. In other scenarios, however, the open space is quite small, suggesting a need for further model-building and/or non-standard cosmologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Calorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data

The MicroBooNE liquid argon time projection chamber located at Fermilab is a neutrino experiment dedicated to the study of short-baseline oscillations, the measurements of neutrino cross sections in liquid argon, and to the research and development of this novel detector technology. Accurate and precise measurements of calorimetry are essential to the event reconstruction and are achieved by leveraging the TPC to measure deposited energy per unit length along the particle trajectory, with mm resolution. We describe the non-uniform calorimetric reconstruction performance in the detector, showing dependence on the angle of the particle trajectory. Such non-uniform reconstruction directly affects the performance of the particle identification algorithms which infer particle type from calorimetric measurements. This work presents a new particle identification method which accounts for and effectively addresses such non-uniformity. The newly developed method shows improved performance compared to previous algorithms, illustrated by a 93.7% proton selection efficiency and a 10% muon mis-identification rate, with a fairly loose selection of tracks performed on beam data. The performance is further demonstrated by identifying exclusive final states in ν μ CC interactions. While developed using MicroBooNE data and simulation, this method is easily applicable to future LArTPC experiments, such as SBND, ICARUS, and DUNE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Diurnal cycle of precipitation over global monsoon systems in CMIP6 simulations

Accurate simulation of the diurnal cycle of precipitation over different climate regimes, including global monsoon systems, is an ongoing challenge for current state-of-the-art climate models. Here, in this study, the diurnal cycles of summertime precipitation from 21 CMIP6 historical simulations are evaluated with the NASA IMERG data via the diurnal harmonic amplitude and phase from the Fourier analysis in seven regional monsoon systems: Northern and Southern Africa monsoons, South Asia monsoon, East Asia monsoon, Australia monsoon, and North and South America monsoons. Particularly, we focus on four subregions including ocean, coastal ocean, land, and coastal land considering the different underlying physical processes. It is found that the CMIP6 historical simulations perform fairly well on reproducing the diurnal cycle of precipitation over ocean and coastal ocean, while the simulated diurnal harmonic phase and amplitude over land and coastal land show larger biases and model spread compared to biases over ocean and coastal ocean. The simulation of precipitation diurnal cycle is substantially improved in the multi-model mean of both CMIP6 historical and CMIP6 AMIP simulations compared with that of CMIP5 historical simulations. But the model bias of precipitation diurnal cycle is in general similar between CMIP6 AMIP and CMIP6 historical simulations, which suggests that the impact of the interactive ocean on the simulated diurnal precipitation averaged over a large domain is generally minor. The influence of model resolution on the diurnal cycle is shown in mixed directions across various subregions, and significant improvement from the low- to high-resolution models is only notable over coastal ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds

Abstract Quantifying the relative influence of factors and processes controlling riverine ecosystem function is essential to predicting future conditions under global change. Dissolved organic matter (DOM) is a fundamental component of riverine ecosystems that fuels microbial food webs, influences nutrient and light availability, and represents a significant carbon flux globally. The heterogeneous nature of DOM molecular composition and its propensity for interaction (i.e., functional diversity) can characterize riverine ecosystem function across spatiotemporal scales. To investigate fundamental drivers of DOM diversity, we collected seasonal water samples from 42 nested locations within five watersheds spanning multiple watershed sizes (~ 5 to 30,000 km 2 ) across the United States. Patterns in DOM molecular richness, aromaticity, relative abundance of N-containing formulas, and putative biochemical transformations derived from high-resolution mass spectrometry were assessed across gradients of explanatory variables associated with watershed characteristics (e.g., watershed area, water residence time, land cover). We found that putative biochemical transformations were more strongly related to explanatory variables across watersheds than common bulk DOM parameters and that watershed area, surface water residence time and derived Damköhler numbers representing DOM reactivity timescales were strong predictors of DOM diversity. The data also indicate that catchment-specific land cover factors can significantly influence DOM diversity in diverging directions. Overall, the results highlight the importance of considering water residence time and land cover when interpreting longitudinal patterns in DOM chemistry and the continued challenge of identifying generalizable drivers that are transferable across watershed and regional scales for application in Earth system models. This work also introduces a Findable Accessible Interoperable Reusable (FAIR) dataset (> 300 samples) to the community for future syntheses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Influence of Molybdenum on Rapid Solidification Microstructure and Microsegregation in Primary Ferrite Solidified Stainless Steel

Due to the widespread use and familiarity of austenitic stainless steels in many industries these alloys are often the first materials used when adapting new processing techniques. The rapid cooling and solidification rates that occur during fusion based additive manufacturing processes like powder bed fusion cause a fundamental shift in the solidification behavior of the material. While the effects that Cr and Ni have on the microstructure have been fairly well documented across a range of solidification conditions, the impact of alloying elements like Mo are not as well understood at rapid solidification rates. For this study, four custom stainless steel alloy feedstocks were made with targeted modification of the Cr and Mo concentrations to maintain a constant Cr/Ni eq ratio of ~1.7. Two-piston splat quenching was used to produce rapidly solidified samples and the solidification mode, phase, and cell size were investigated. Solidification rates were estimated to be between 0.4 and 1.5m/s. A comparison of the microsegregation and partitioning behavior of Cr, Ni and Mo in ferrite solidified material was also performed for the different alloy compositions. Variations of the Mo concentration between each feedstock showed no measurable influence on the solidification/cooling rates, solidification morphology, or the partitioning of Mo. Furthermore, higher concentrations of Mo were found to significantly increase the amount of ferrite phase in the microstructure by suppressing the ferrite to austenite massive transformation.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Optimization of CCT Equations Using Calculated Grain Boundary Soluble Compositions for the Simulation of Austenite Decomposition of Steels

New CCT equations have been developed and optimized to simulate the start temperatures of the austenite decomposition process in low-alloyed steels using experimental CCT data published in the literature. Exceptionally, this optimization does not apply the nominal compositions of the steels, but the corresponding soluble compositions of the grain boundaries calculated using IDS software, depending on the reported austenitization treatments of the steels. These compositions, rather than the nominal ones, are expected to control the start of the austenite decomposition, which usually initiates at the grain boundaries. The new optimization treatment takes into account the solute microsegregation and the possible precipitate formation. Using IDS software, the new equations were validated with new experimental CCT data. Agreement was good not only for the austenite decomposition start temperatures, but also for the final phase fractions, indicating fairly reasonable predictions of phase transformation kinetics by the IDS. In addition, IDS simulations were compared with the experimental CCT data of five high-carbon steels, applying both the new equations based on grain boundary soluble compositions as well as the equations based on the nominal compositions. With the same experimental CCT data used in optimization, better agreement was obtained with the new equations, indicating the importance of determining the soluble compositions at the grain boundaries where the austenite decomposition process is likely to begin.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ending the Energy-Poverty Nexus: An Ethical Imperative for Just Transitions

Arguments for a just transition are integral to debates about climate change and the drive to create a carbon-neutral economy. There are currently two broad approaches rooted in ethics and justice for framing just energy transitions. The first can be described as internal to the transition and emphasizes the anticipation, assessment, and redressing of harms created by the transition itself and the inclusion in transition governance of groups or communities potentially harmed by its disruptions. In this article, we propose a second approach to ethics and justice in an energy transition, which we describe as systemic or societal in scope. This approach complements attention to the proximate dynamics and impacts of the transition process with a focus on the distant societal and economic outcomes the transition brings into being and how they compare to conditions prior to the transition. It poses the question: do the transformative social, economic, and technological changes wrought by energy systems create more just societies and economies, or do they instead reinforce or recreate long-standing injustices and inequalities? We illustrate this approach with an assessment of one of the most significant existing forms of energy injustice: the energy-poverty nexus. We argue that the energy-poverty nexus reflects configurations of socio-energy systems that create complex, extractive feedbacks between energy insecurity and economic insecurity and, over time, reinforce or exacerbate poverty. We further argue that just energy transitions should work to disentangle these configurations and re-design them so as to create generative rather than extractive feedbacks, thus ending the energy-poverty nexus and creating long-term outcomes that are more just, equitable, and fair.

14 SOLAR ENERGY↗
DOE OSTI2023

A Workflow for Accelerating Multimodal Data Collection for Electrodeposited Films

Abstract Future machine learning strategies for materials process optimization will likely replace human capital-intensive artisan research with autonomous and/or accelerated approaches. Such automation enables accelerated multimodal characterization that simultaneously minimizes human errors, lowers costs, enhances statistical sampling, and allows scientists to allocate their time to critical thinking instead of repetitive manual tasks. Previous acceleration efforts to synthesize and evaluate materials have often employed elaborate robotic self-driving laboratories or used specialized strategies that are difficult to generalize. Herein we describe an implemented workflow for accelerating the multimodal characterization of a combinatorial set of 915 electroplated Ni and Ni–Fe thin films resulting in a data cube with over 160,000 individual data files. Our acceleration strategies do not require manufacturing-scale resources and are thus amenable to typical materials research facilities in academic, government, or commercial laboratories. The workflow demonstrated the acceleration of six characterization modalities: optical microscopy, laser profilometry, X-ray diffraction, X-ray fluorescence, nanoindentation, and tribological (friction and wear) testing, each with speedup factors ranging from 13–46x. In addition, automated data upload to a repository using FAIR data principles was accelerated by 64x.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Do agrivoltaics improve public support for solar? A survey on perceptions, preferences, and priorities

Abstract Agrivoltaic systems integrate agricultural production with solar photovoltaic electricity generation. Given the proven technical, economic, and environmental co-benefits provided by agrivoltaic systems, increased proliferation is anticipated, which necessitates accounting for the nuances of community resistance to solar development on farmland and identifying pathways for mitigation. Minimizing siting conflict and addressing agricultural communities’ concerns will be key in continued deployment of agrivoltaics, as localized acceptance of solar is a critical determinant of project success. This survey study assessed if public support for solar development increases when energy and agricultural production are combined in an agrivoltaic system. Results show that 81.8% of respondents would be more likely to support solar development in their community if it integrated agricultural production. This increase in support for solar given the agrivoltaic approach highlights a development strategy that can improve local social acceptance and the deployment rate of solar. Survey respondents prefer agrivoltaic projects that a) are designed to provide economic opportunities for farmers and the local community b) are not located on public property c) do not threaten local interests and d) ensure fair distribution of economic benefits. Proactively identifying what the public perceives as opportunities and concerns related to agrivoltaic development can help improve the design, business model, and siting of systems in the U.S.

Pascaris, Alexis S. (ORCID:0000000253806927)↗
DOE OSTI2022

Electrifying High-Efficiency Future Communities: Impact on Energy, Emissions, and Grid

To combat climate change and meet decarbonization goals, the building sector is improving energy efficiency and electrifying end uses to reduce carbon emissions from fossil fuels. All-electric buildings are becoming a trend among new constructions, introducing opportunities for decarbonization but also technical challenges and research gaps. For instance, further investigation is needed to understand how the adoption of energy efficiency measures (EEMs) and distributed energy resources (DERs) in all-electric communities would affect energy consumption, carbon emissions, and grid planning. This paper presents a case study of a mixed-use, all-electric community located in Denver, Colorado. We use URBANopt TM , a physics-based urban energy modeling platform to model the community and then evaluate the impact of EEMs and DERs (i.e., photovoltaics [PV], electric vehicles [EVs], and batteries) on the community's energy usage, carbon emissions, and peak demand. The results show that adding EEMs and PV led to both energy consumption and carbon emissions reductions across all building types. However, we saw fairly limited impact of EEMs and PV on buildings' peak demand in our case. Additionally, due to overnight EV charging activities and higher grid carbon intensity at night, the carbon emissions in multifamily buildings have a noticeable increase compared to scenarios without vehicles. Finally, the addition of batteries helped reduce peak demand by 11%-29%. The modeling workflow and evaluation methods can be applied to similar communities to evaluate their performance and the effect of integrating EEMs and DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Toward efficient single-atom catalysts for renewable fuels and chemicals production from biomass and CO 2

Transformation of biomass and CO 2 into renewable value-added chemicals and fuels has been identified as a promising strategy to fulfill high energy demands, lower greenhouse gas emissions, and exploit under-utilized resources. Cost-effective and performance-efficient catalysts are of great importance to lowering the conversion cost of biomass and CO 2 . Significant progress has been made to advance the catalyst design for these processes, with metal catalysts playing a critical role in many involved catalytic reactions. Traditional nanoparticle-based metal catalysts still require improvement in metal utilization rates, stability, and selectivity tunability. Single-atom catalysts, which have maximum atomic efficiency and a uniform and tunable metal center, as well as an adjustable metal-support interaction, provide potential opportunities to boost catalyst efficiency and thermal stability. Their well-defined and uniform structure also provides advantages to fundamental studies for understanding of the intrinsic reaction mechanism and site requirement in biomass and CO 2 conversion. In this article, we summarize and highlight the recent advances in converting biomass and CO 2 to renewable fuels and chemicals using single-atom catalysts. We discuss the design principles of single-atom catalysts and their potential applications to biomass and CO 2 upgrading as well as the origins of catalytic activity. Moreover, we compare the catalytic efficiency of various catalysts reported thus to provide a fair assessment of these catalysts. Finally, perspectives are given on the interesting fields that may guide future studies.

09 BIOMASS FUELS↗
DOE OSTI2021

Blockchain Smart Contract Reference Framework and Program Logic Architecture for Transactive Energy Systems

This paper proposes a reference framework for a transactive energy market based on blockchain. The framework was designed based on the engineering requirements of a distribution-scale market; including participant needs, expected market transactions, and the cybersecurity constructs required to support a fair, secure and efficient market operation. It leverages the existing blockchain primitives to provide clear value propositions to the transactive market, including identity management (access control), data security (integrity), resiliency (decentralization, scalability and performance). The validity of the proposed framework is demonstrated using a real-time 5-min double-auction market. The results highlight its benefits while providing strong validation of applicability to blockchain within transactive energy systems.

Gourisetti, Sri Nikhil Gupta↗
DOE OSTI2026

Design trade-offs for residential retail tariffs and virtual power plants

Retail rate design and virtual power plants (VPPs) have the potential to shift customer electricity demand and provide economic benefits to utility customers. As the adoption of distributed energy resources (DERs) and flexible loads increases, retail tariff and program design can impact Bonbright's rate design principles including affordability, fairness, and economic efficiency. We model the effects of residential retail rates and VPP programs on power system costs in Massachusetts under a potential future system with high renewable energy and DER adoption. We model interactions among retail rate design, demand flexibility, and utility costs and identify trade-offs across different rate designs and VPP programs. We estimate that time-of-use (TOU) rates and VPP programs designed to avoid critical peak rates can lower overall system costs by 3.5 %-4.8 %. These lower costs translate to lower electricity bills for 62 %-91 % of customers, depending on the scenario. Although TOU rates with a critical peak VPP program can benefit all customer segments and are economically efficient, a VPP program with flat rates leads to the lowest overall bills for customers. We find that customers with loads that align with peak demand and who participate in critical peak VPP programs can underpay for their contribution to utility costs and shift costs to other customers. While our assumptions about mandatory TOU and/or critical peak pricing likely impact the magnitude of the results, the results highlight the trade-offs of these tariffs and programs and the importance of tariff and program design as demand becomes more flexible and responsive.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A chemistry-informed hybrid machine learning approach to predict metal adsorption onto mineral surfaces

Historically, surface complexation model (SCM) constants and distribution coefficients (K d ) have been employed to quantify mineral-based retardation effects controlling the fate of metals in subsurface geologic systems. Our recent SCM development workflow, based on the Lawrence Livermore National Laboratory Surface Complexation/Ion Exchange (L-SCIE) database, illustrated a community FAIR data approach to SCM development by predicting uranium(VI)-quartz adsorption for a large number of literature-mined data. Here, we present an alternative hybrid machine learning (ML) approach that shows promise in achieving equivalent high-quality predictions compared to traditional surface complexation models. At its core, the hybrid random forest (RF) ML approach is motivated by the proliferation of incongruent SCMs in the literature that limit their applicability in reactive transport models. Our hybrid ML approach implements PHREEQC-based aqueous speciation calculations; values from these simulations are automatically used as input features for a random forest (RF) algorithm to quantify adsorption and avoid SCM modeling constraints entirely. Named the LLNL Speciation Updated Random Forest (L-SURF) model, this hybrid approach is shown to have applicability to U(VI) sorption cases driven by both ion-exchange and surface complexation, as is shown for quartz and montmorillonite cases. The approach can be applied to reactive transport modeling and may provide an alternative to the costly development of self-consistent SCM reaction databases.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

n-Type doping of a solution processed p-type semiconductor using isoelectronic surface dopants for homojunction fabrication

The p-n junction is one of the fundamental requirements for a practical semiconductor-based electronic device. Designing a heterojunction comprising of dissimilar p-type and n-type semiconductors calls for careful energy level considerations, both when selecting the semiconductor materials as well as the metal contacts. A homojunction based on a single semiconductor simplifies this task, as energy levels of the p-type and n-type materials are already fairly similar, allowing for easier selection of contacts. Traditionally, homojunctions rely on doping of a bulk semiconductor to achieve p- and n-type transport through controlled addition of aliovalent dopants via energy-intensive processes such as ion implantation or thermal annealing. Exact control of doping in nanocrystalline semiconductors is significantly more challenging, due to self-purification effects. However, owing to their large surface areas, surface moieties can be utilized to both dope the nanostructures as well as tune their energy levels. Here, we present a facile technique based on an isoelectronic surface dopant in order to achieve p- and n-type materials based on the same semiconductor. We show that thin p-type colloidal Bi 2 Te 3 nanowires can be switched to n-type through surface functionalization, thus increasing the availability of new nanocrystalline solution-processable p-n homojunctions.

42 ENGINEERING↗