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At least 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Data for Spatial Analysis of Cell Patterning to Aid Genetic and Phenotypic Understanding of Grass Stomatal Density: A Case Study in Maize

Biological processes involve complex hierarchies where composite traits result from multiple component traits. However, holistically understanding of how sets of component traits interact to underpin genotype-to-phenotype relationships is generally lacking. Stomatal density (SD) is a tractable model system for exploring how high-throughput phenotyping (HTP) data could be exploited by a new spatial analysis approach to better understand a developmentally and functionally important trait. SD is a composite trait, resulting from various components related to cell identity and size, which are themselves governed by a series of spatio-developmental processes. Data from 192 recombinant inbred lines of maize [Zea mays (L.)] were analyzed by a new stomatal patterning phenotype (SPP) to (1) describe the average spatial probability distribution of the nearest neighboring stomata; (2) derive a core set of component traits related to cell size, cell packing, and positional probabilities; (3) build a structural equation model of component traits underlying SD; and (4) identify stomatal patterning quantitative trait loci (QTL). The core set of SPP-derived traits explained 74% of the variation in SD. Analyzing SPP component traits allowed some loci previously identified as generic SD QTL to be recognized as specific to lateral versus longitudinal elements of stomatal patterning. Therefore, this study highlights how novel insights can be gained by decomposing a composite trait (e.g., SD) into a set of component traits that were present in HTP data but not previously exploited.

AI/ML↗
DOE OSTI2014

Technology Solutions Case Study: Initial and Long-Term MOvement of Cladding Installed Over Exterior Rigid Insulation

Changes in the International Energy Conservation Code (IECC) from 2009 to 2012 have resulted in the use of exterior rigid insulation becoming part of the prescriptive code requirements. With more jurisdictions adopting the 2012 IECC, builders will be required to incorporate exterior insulation in the construction of their exterior wall assemblies. For thick layers of exterior insulation (levels greater than 1.5 inches), the use of wood of furring strips attached through the insulation back to the structure has been used by many contractors and designers as a means to provide a convenient cladding attachment location. However, there has been resistance to its widespread implementation due to a lack of research and understanding of the mechanisms involved and potential creep effects of the assembly under the sustained dead load of a cladding. This research conducted by Building Science Corporation evaluated the system mechanics and long-term performance of this technique.

BSC↗
DOE OSTI2019

Modelling of air handling unit subsystem in a commercial building

To improve energy efficiency of the Air Handling Unit (AHU), there is a need for a system to monitor energy performance of the AHU in real time, to optimize operation for minimum energy consumption and to calculate energy saving. A mechanical model was created to analyze the performance of subsystems in an AHU and was validated using actual data collected from AHU operation via a wireless monitoring system. Algorithms have been developed to identify malfunctions and estimate the savings if malfunctions are corrected. Here, the model detects control related malfunctions, such as simultaneously turning on the cooling coil and the pre-heating coil. According to the mechanical model of the case study system, a total of 63,455 kWh are wasted within the cooling coil and the pre-heating coil due to this type of control malfunction. Furthermore, the mechanical model can identify other energy savings opportunities due to set point changes; in the case study system, this feature revealed a total of 77,141 kWh energy saving during the same study period. The design, integration, and validation of the mechanical model are described, analyzed, and justified in this paper.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Dynamic Material Flow Analysis of Silicon Photovoltaic Modules to Support a Circular Economy Transition

Solar photovoltaics (PV) are the fastest growing renewable energy technologies for clean, cheap, and sustainable electricity generation. To prepare for rapid scale-up, the PV industry needs to project material requirements to build out all aspects of the supply chain appropriately and plan to handle large volumes of module waste. Impacts of deploying different material circularity strategies to reduce waste and conserve primary resources need to be quantified to inform sustainable material management. Here, we introduce the photovoltaic dynamic material flow analysis (PV DMFA) model based on PV electricity generation. The model quantifies material flows and stocks in the cradle-to-cradle life cycles of utility-scale c-Si PV systems in the United States through 2100. We present case studies for solar flat glass and aluminum frame materials under various scenarios to project the impacts of PV performance, reliability, and processing parameters, material circularity strategies, and module design shifts. In the absence of circularity measures, ~100 million MT of flat glass and ~12 million MT of aluminum would be needed for PV installations by 2100 to meet projected growth in domestic utility PV demand to nearly 1000 TWh in 2100. With optimistic but feasible improvements in efficiency, reliability, and circularity, material intensity and waste could be reduced by nearly 50%. Efficient module collection, minimally intrusive recycling, and careful scrap handling and cleaning could improve material circularity in the PV value chain. This model serves as a sustainability data support tool that may aid in the circular economy transition for PV systems.

circular economy↗
DOE OSTI2017

Comparison of typical year and multiyear building simulations using a 55-year actual weather data set from China

Weather has significant impacts on the thermal environment and energy use in buildings. Thus, accurate weather data are crucial for building performance evaluations. Traditionally, typical year data inputs are used to represent long-term weather data. However, there is no guarantee that a single year represents the changing climate well. In this study, the long-term representation of a typical year was assessed by comparing it to a 55-year actual weather data set. To investigate the weather impact on building energy use, 559 simulation runs of a prototype office building were performed for 10 large cities covering all climate zones in China. The analysis results demonstrated that the weather data varied significantly from year to year. Hence, a typical year cannot reflect the variation range of weather fluctuations. Typical year simulations overestimated or underestimated the energy use and peak load in many cases. With the increase in computational power of personal computers, it is feasible and essential to adopt multiyear simulations for full assessments of long-term building performance, as this will improve decision-making by allowing for the full consideration of variations in building energy use.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Highly Accelerated UV Stress Testing for Transparent Flexible Frontsheets

There are many photovoltaic (PV) applications where lighter weight and/or bendable PV power would be beneficial. This includes the curved surfaces of buildings, buildings with weight limitations, boats, automobiles, or other portable applications. In many of these cases, the bending will be only a single occurrence at installation or the amount of bending, even if repeated, is not dramatic. This allows for crystalline silicon modules to be used. For flexible applications, the dominant material for the frontsheet is polyethylene tetrafluoroethylene (PETFE). As a fluoropolymer it resists soiling, is UV stable, and PETFE is a more mechanically durable fluoropolymer. However, in the interests of keeping costs down, less expensive alternative polymers are desirable. In this study, highly accelerated ultraviolet light and heat stresses are applied to candidate materials and the degradation kinetics are determined to provide information to evaluate their suitability for use in a PV application.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2025

West Coast Offshore Wind Transmission Study

As a primary federal investigation of the utility of transmission to support offshore wind emergence in the Western Interconnect, the West Coast Offshore Wind Transmission study evaluates five distinct West Coast-wide transmission scenarios and trades the economic benefits and costs of six development pathways from 2035 to 2050. In this time, 33 GW of OSW generation and supporting transmission are explored within the context of 350 additional GW of generation to support 100% clean electricity. Geospatial analysis informed plausible transmission topologies and cost estimates. All pathways to intraregional or interregional coordination transmission builds showed more than $\$$14 billion in present value cost savings, with a maximum of $\$$25 billion of savings in the interregional case. These savings are primarily driven by fuel costs and increased availability of power flows enabled by new transmission networks. Key considerations of clean, dispatchable generation options, geographic disaggregation of costs, system reliability reinforcements, resilience, and community values are also presented and discussed.

17 WIND ENERGY↗
DOE OSTI2024

A Proposed Evaluation Framework for New and Emerging Low Embodied-Carbon Concrete Technologies

New opportunities for carbon reductions in buildings create a strong need for a common framework and method for those who design, build and influence construction to evaluate lifecycle carbon reductions from design decisions and technology choices. These opportunities include a wide range of low-embodied-carbon concrete materials being rapidly developed and introduced to the market. How to evaluate these newer materials and technologies has become critical for both public- and private-sector actors seeking to decarbonize building constructions by leveraging the Infrastructure Investment and Jobs Act (IIJA) and Inflation Reduction Act (IRA) funds. We propose an evaluation framework to assess the lifecycle carbon reductions from adoption of these technologies, including a subset of key “must have” (1) technical criteria (embodied carbon level, technology development stage); (2) market criteria (market size, scalability); and (3) financial criteria (cost of technology implementation compared to businessas-usual) from a range of options. We discuss how to use the framework and illustrate it using a “heatmap,” rating score and short case study of a promising technology. We also propose a plan to implement this framework that includes (1) standardized measurement and validation methods for verifying emission reductions from these technologies, and (2) avenues to implement real world demonstrations. We conclude with recommendations for next steps on framework refinement and commercialization strategy development.

Singh, Reshma↗
DOE OSTI2014

Existing Whole-House Solutions Case Study: Community-Scale Energy Modeling - Southeastern United States

Community-scale energy modeling and testing are useful for determining energy conservation measures that will effectively reduce energy use. To that end, IBACOS analyzed pre-retrofit daily utility data to sort homes by energy consumption, allowing for better targeting of homes for physical audits. Following ASHRAE Guideline 14 normalization procedures, electricity consumption of 1,166 all-electric, production-built homes was modeled. The homes were in two communities: one built in the 1970s and the other in the mid-2000s.

ASHRAE GUIDELINE 14↗
DOE OSTI2013

Assessing the Energy Savings of Tankless Water Heater Retrofits in Public Housing

This report describes the methodology, analysis, and findings from a case study of a 110 unit retrofit of gas tankless water heaters in a hot/humid climate in Alachua County, Florida. The housing units had their gas-fired tank type water heaters replaced with gas-fired tankless water heaters as part of a federal program that targeted reduced energy use in public housing.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2011

Existing Whole-House Solutions Case Study: Retrofit of 1915 Home, Dayton, Washington

This case study lists project information, cost and energy efficiency performance data, energy efficiency measures and lessons learned for a 1915 home in eastern Washington audited by Pacific Northwest National Laboratory for an energy retrofit. The asbestos covered diesel boiler was left in place in the basement and a new SEER 16, HSPF 9.4 ductless heat pump with four inside heads was added to cut energy costs over $2,000/year.

Building America↗
DOE OSTI2015

Determinants of land take at the regional scale: a study concerning Sardinia (Italy)

In its “Roadmap to a Resource Efficient Europe” (Communication COM(2011) 571 of 20 September 2011), the European Commission (EC) established an ambitious goal for the European Union (EU), that of achieving no land take by 2050; towards this aim, a key milestone for the year 2020 was set, by stating that European policies in the programming period 2014–2020 ought to consider both their direct and their indirect impacts on land use in the EU. Within this framework, this paper builds upon the findings of a previous paper (Zoppi and Lai, 2014), in which we estimated the magnitude of land take over a short period of time (2003–2008) in Sardinia, an Italian NUTS2 region, and we assessed whether and how land take is related to a set of variables that are regarded as important determinants in the literature, such as parcel size, accessibility, and proximity to main cities and towns, to the coastline, or to protected areas. In this paper we study the land-taking process taking Sardinia as a case study, in two larger time periods, 1960–1990 and 1990–2008. We assess if, and to what extent, these factors reveal similar, or different, effects in the two periods, and try to identify consistencies concerning the determinants of land take. - Highlights: • Population density and parcel size significantly affect the magnitude of land take. • The presence of nature conservation areas hinders land taking processes. • Extensive urbanization might effectively preserve non-artificial land. • Balanced accessibility of settlements and nature conservation regional policies can effectively contrast land take. • Size of non-artificial land parcels that become artificial is negatively and significantly connected to land take.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Creep anisotropy modeling and uncertainty quantification of an additively manufactured Ni-based superalloy

The advantages offered by additive manufacturing over traditional processes has driven a great deal of industrial and academic interest in recent years. However, the process is relatively new and requires additional investigation to become sufficiently mature for wide scale industrial adoption. Electron beam melting powder bed fusion is one technology that has shown promise for fabricating high temperature resistant materials such as nickel based superalloys. The resulting microstructures typically exhibit a strong fiber texture in the build direction giving rise to anisotropic time-dependent deformation behavior. In order to accelerate the qualification of these materials for industrial adoption accurate numerical models are needed for simulating their behavior. In this work a crystal plasticity model including non-Schmid effects is presented for capturing creep anisotropy observed in additively manufactured IN738LC. The model is calibrated via a probabilistic framework where model parameters are treated as random variables. An iterative sequential design strategy is utilized to efficiently identify the probability density of the unknown model parameters. As a case study the model is utilized to investigate the behavior of randomly oriented equiaxed grain clusters sometimes observed embedded in the additively manufactured columnar structure. A synthetic realization is simulated and uncertainty is propagated through to the full-field response. Results indicate that these features are the source of significant creep relaxation and strain accumulation which partially explains observed grain boundary decohesion at these locations.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Scalable Screening of Soft Matter: A Case Study of Mixtures of Ionic Liquids and Organic Solvents

Room-temperature ionic liquids (RTILs) are a class of organic salts that are liquid at room temperature. Their physiochemical properties, including low vapor pressure and wide electrochemical stability window, have expedited their use as electrolytes in many electrochemical applications; yet, the slow transport properties of many RTILs have limited their utility in some applications. This issue is often mitigated by solvating ionic liquids in neutral organic solvents. To date, however, solvent interactions have only been explored for a small number of solvents, particularly acetonitrile and propylene carbonate, at only a few compositions. Here, we use molecular dynamics simulations in the context of a computational screening approach to study mixtures of ionic liquids in many different solvents at a range of concentrations. Building on prior work, we again find that ionic liquid diffusivity increases monotonically with greater solvent concentration. In contrast to prior work, we find that pure solvent diffusivity, not polarity, is the most influential solvent property on mixture behavior. We also explore the concentration dependence of ionic conductivity and find maxima at intermediate concentrations. Experimental conductivity measurements, inspired by the computational screening study, support this observation with qualitatively consistent results. These results can further guide the selection of solvents for electrochemical applications of RTILs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Designing accurate emulators for scientific processes using calibration-driven deep models

Abstract Predictive models that accurately emulate complex scientific processes can achieve speed-ups over numerical simulators or experiments and at the same time provide surrogates for improving the subsequent analysis. Consequently, there is a recent surge in utilizing modern machine learning methods to build data-driven emulators. In this work, we study an often overlooked, yet important, problem of choosing loss functions while designing such emulators. Popular choices such as the mean squared error or the mean absolute error are based on a symmetric noise assumption and can be unsuitable for heterogeneous data or asymmetric noise distributions. We propose Learn-by-Calibrating, a novel deep learning approach based on interval calibration for designing emulators that can effectively recover the inherent noise structure without any explicit priors. Using a large suite of use-cases, we demonstrate the efficacy of our approach in providing high-quality emulators, when compared to widely-adopted loss function choices, even in small-data regimes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

How galaxies populate halos in extreme density environments: An analysis of the halo occupation distribution in SDSS

Recent works have shown that the properties of galaxy populations in simulated dark matter halos vary with large-scale environments. These results suggest a variation in the halo occupation distribution (HOD) in extreme density environments since the dynamical and astrophysical conditions prevailing in these regions may significantly affect the formation and evolution of their halos and residing galaxies, influencing the mean number of satellite galaxies. To analyse these effects, we identify cosmic voids and future virialised structures (FVS) in the Sloan Digital Sky Server Data Release 12 (SDSS-DR12) and estimate the HOD within these super-structures using group catalogues as dark matter halo proxies. Our goal is to use observational galaxy data to characterise the HOD within cosmic voids and FVS, explore the different properties of these galaxies populations and compare them with the general results outside these super-structures. We use a publicly available observational galaxy catalogue with information on redshifts, positions, magnitudes and other astrophysical features to build a volume complete galaxy sample and identify cosmic voids and FVS. Using a publicly available galaxy group catalogue as a proxy to dark matter halos, we compute the HOD within both types of super-structures for different absolute magnitude thresholds. We also study the dependence on the results on the main void and FVS properties, density and volume. We also analysed the main characteristics of the stellar content of galaxies inside these extreme-density regions such as the mean stellar age and the galaxy light concentration index. In all cases, we compare the results with those derived from the Field sample, defined by objects outside both types of environments. Inside cosmic voids, we find a strong decrease in HOD concerning the Field results. In the most extreme cases, the mean number of satellites fall to ~ 50%. Inside FVS, the HOD shows a significant increase to the Field, with a ~ 40% excess in the mean number of satellites. These results are present for the different galaxy luminosity ranges explored. In both environments, the differences with respect to the Field increases for the extreme values of the density environments. However, we obtain no signs of variations related to intrinsic characteristics of the super-structures, indicating that the effects depend mainly on the density of the large-scale environment. In addition, we find that the cumulative distribution of the mean age of stars of the central galaxy also varies in the different regions, this suggests that the history of the formation of the dark matter halos may be different. Finally, we explore the HOD for the 25% youngest (oldest) galaxies, based on the mean age of their stars. We find that for the low-mass groups the youngest galaxies are only present inside voids and are generally central galaxies. On the other hand, for the high-mass groups the FVS environments show the same increase in the HOD concerning the Field as previously mentioned. We find that cosmic voids lack a significant fraction of galaxies with the oldest stellar population.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

A unified theory of quasibound states

We report a formalism for the study of quasibound states, defined here broadly as those states having a connectedness to true bound states through the variation of some physical parameter. The theory admits quasibound states with real energies (stationary quasibound states) and quantum resonances within the same framework, and makes a clean distinction between these states and those of the associated continuum. The approach taken here builds on our earlier work by clarifying several crucial points and extending the formalism to encompass a variety of continuous spectra, including those with degeneracies. The theory is illustrated by examining several cases pertinent to applications widely discussed in the literature. The related issue of observing stationary quasibound states also is addressed. We argue that the Adiabatic Theorem of quantum mechanics not only establishes the criteria necessary for their detection, but also engenders a method for assigning to them a level width that is sufficiently distinct from that of quantum resonances so as to allow the two to be differentiated experimentally.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Integrated Multi-Scale Data Analytics and Machine Learning for the Distribution Grid

We consider the field of machine learning and where it is both useful, and not useful, for the distribution grid and buildings interface. While analytics, in general, is a growing field of interest, and often seen as the golden goose in the burgeoning distribution grid industry, its application is often limited by communications infrastructure, or lack of a focused technical application. Overall, the linkage of analytics to purposeful application in the grid space has been limited. In this paper we consider the field of machine learning as a subset of analytical techniques, and discuss its ability and limitations to enable the future distribution grid. To that end, we also consider the potential for mixing distributed and centralized analytics and the pros and cons of these approaches. There is an exponentially expanding volume of measured data being generated on the distribution grid, which, with appropriate application of analytics, may be transformed into intelligible, actionable information that can be provided to the right actors - such as grid and building operators, at the appropriate time to enhance grid or building resilience, efficiency, and operations against various metrics or goals - such as total carbon reduction or other economic benefit to customers. While some basic analysis into these data streams can provide a wealth of information, computational and human boundaries on performing the analysis are becoming significant, with more data and multi-objective concerns. Efficient applications of analysis and the machine learning field are being considered in the loop. This paper describes benefits and limits of present machine-learning applications for use on the grid and presents a series of case studies that illustrate the potential benefits of developing advanced local multi-variate analytics machine-learning-based applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗