Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “case studies”

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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Nonpigmented PsbR is involved in the integrity of excitation landscape in higher plant photosystem II, a case study in Arabidopsis thaliana and a mutant

PsbR is a nonpigmented 10 kDa protein in Photosystem II (PSII) in algae and plants. A recent structural study clarified its enigmatic structural location in a Photosystem II megacomplex that has baffled the community for more than four decades. Our current study interrogates whether absence of PsbR affects the overall dynamics of excitation energy migration within light harvesting complexes (LHC) and PSII super assemblies using highly-active PSII membrane particles, so-called BBY particles, isolated from a PsbR deletion mutant (ΔPsbR) of Arabidopsis thaliana. A femto-second (fs)-time-resolved transient absorption experimentation recorded at 77 K with selective excitation of Chl b which is exclusively present in LHCs enabled us to resolve the temporal differences in LHC→LHC and LHC→PSII excitation energy transfer steps. By applying specific target spectro-kinetic models to the transient absorption datasets, we demonstrated that the time constants of Chl a LHC → Chl a LHC excitation transfer significantly elongates in the ΔPsbR LHC-PSII particles, suggestive of the decreased aggregation level of photosynthetic proteins in the mutant. These findings highlight excitation energy transfer integrity in LHC-PSII assembly is not only determined by the pigmented light-harvesting complexes, but also synergistically by the nonpigmented PSII components. Furthermore, the disturbed integrity in dynamics of excitation energy transfer pathway within LHC-PSII supercomplex is discussed in the context of the altered LHC-PSII megacomplexes type I and II architectures which result from the absence of the PsbR protein in higher plant PSII.

Chlorophyll↗
DOE OSTI2025

Scalable training of trustworthy and energy-efficient predictive graph foundation models for atomistic materials modeling: a case study with HydraGNN

We present our work on developing and training scalable, trustworthy, and energy-efficient predictive graph foundation models (GFMs) using HydraGNN, a multi-headed graph convolutional neural network architecture. HydraGNN expands the boundaries of graph neural network (GNN) computations in both training scale and data diversity. It abstracts over message passing algorithms, allowing both reproduction of and comparison across algorithmic innovations that define nearest-neighbor convolution in GNNs. This work discusses a series of optimizations that have allowed scaling up the GFMs training to tens of thousands of GPUs on datasets consisting of hundreds of millions of graphs. Our GFMs use multitask learning (MTL) to simultaneously learn graph-level and node-level properties of atomistic structures, such as energy and atomic forces. Using over 154 million atomistic structures for training, we illustrate the performance of our approach along with the lessons learned on two state-of-the-art US Department of Energy (US-DOE) supercomputers, namely the Perlmutter petascale system at the National Energy Research Scientific Computing Center and the Frontier exascale system at Oak Ridge Leadership Computing Facility. The HydraGNN architecture enables the GFM to achieve near-linear strong scaling performance using more than 2000 GPUs on Perlmutter and 16,000 GPUs on Frontier.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Evaluating the energy impact potential of energy efficiency measures for retrofit applications: A case study with U.S. medium office buildings

Quantifying the energy savings of various energy efficiency measures (EEMs) for an energy retrofit project often necessitates an energy audit and detailed whole building energy modeling to evaluate the EEMs; however, this is often cost-prohibitive for small and medium buildings. In order to provide a defined guideline for projects with assumed common baseline characteristics, this paper applies a sensitivity analysis method to evaluate the impact of individual EEMs and groups these into packages to produce deep energy savings for a sample prototype medium office building across 15 climate zones in the United States. We start with one baseline model for each climate zone and nine candidate EEMs with a range of efficiency levels for each EEM. Three energy performance indicators (EPIs) are defined, which are annual electricity use intensity, annual natural gas use intensity, and annual energy cost. Then, a Standard Regression Coefficient (SRC) sensitivity analysis method is applied to determine the sensitivity of each EEM with respect to the three EPIs, and the relative sensitivity of all EEMs are calculated to evaluate their energy impacts. For the selected range of efficiency levels, the results indicate that the EEMs with higher energy impacts (i.e., higher sensitivity) in most climate zones are high-performance windows, reduced interior lighting power, and reduced interior plug and process loads. However, the sensitivity of the EEMs also vary by climate zone and EPI; for example, improved opaque envelope insulation and efficiency of cooling and heating systems are found to have a high energy impact in cold and hot climates.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Developing occupant archetypes within urban low-income housing: A case study in Mumbai, India

Rapid urbanization pressure and poverty have created a push for affordable housing within the global south. The design of affordable housing can have consequences on the thermal (dis)comfort and behaviour of the occupants, hence requiring an occupant-centric approach to ensure sustainability. This paper investigates occupant behaviour within the urban poor households of Mumbai, India and its impact on their thermal comfort and energy use. This study is a first-of-its-kind attempt to explore the socio-demographic characteristics and energy-related behaviour of low-income occupants within Indian context. Three occupant archetypes, Indifferent Consumers; Considerate Savers; and Conscious Conventionals, were identified from the behavioural and psychographic characteristics gathered through a transverse field survey. A two-step clustering approach was adopted for occupant segmentation that highlighted considerable diversity in occupants’ adaptation measures, energy knowledge, energy habits, and their pro-environmental behaviour within similar socio-economic group. Building energy simulation of the representative archetype behaviour estimated up to 37% variations for air-conditioned and up to 8% variation for fan-assisted naturally ventilated housing units during peak summer months. The results from this study establish the significance of occupant factors in shaping energy demand and thermal comfort within low-income housing and pave way for developing occupant-centric building design strategies to serve this marginalized population. The developed low-income occupant archetypes would be useful for architects and energy modelers to generate realistic energy use profiles and improve building performance simulation results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Using yttrium as an indicator to estimate total rare earth element concentration: a case study of anthracite-associated clays from northeastern Pennsylvania

Abstract This study demonstrated using yttrium (Y) as an indicator to estimate the total rare earth element and Y contents (REY) in coal-associated samples and to facilitate selection of samples with high REY assays in a fast and inexpensive manner. More than 10 anthracite-associated samples were collected from each of three Pennsylvanian sites (sites B, J and C) based on Thorium gamma ray logging suggesting high REY content. Several samples from each site were analyzed by ICP-MS to determine the rare earth distribution patterns and to establish the site-specific linear equations of Y and REY. The Y contents of the remaining samples were measured by a portable X-ray fluorescence analyzer, and the REY values were estimated based on the site-specific linear equation developed earlier. R-squared values above 0.70 were obtained for all the estimation equations from all three sites on both a whole sample basis and an ash basis. Previously, ash content has been widely used as an indicator of high REY content. This may not be applicable for a specific site. Site B in this study is an example where ash contents could not be statistically correlated with REY, so using Y for estimation is more applicable. The demonstrated sample screening process is suitable for samples from sites that share more similar distribution patterns (either MREY or LREY or HREY) as well as for samples from sites that share multiple distribution patterns (LREY/MREY/HREY) depending on the desirable accuracy. The demonstrated process lowers the analytical cost from $70 to 80 dollars per sample to $10–15 per sample while significantly reducing the processing time and acid consumption for ICP digestion. This is particularly true when a relatively large sample size is involved, for example, 100 samples from one site analyzed by ICP-MS/OES.

Yang, Xiaojing↗
DOE OSTI2024

Mineral and fluid transformation of hydraulically fractured shale: case study of Caney Shale in Southern Oklahoma

This study explores the geochemical reactions that can cause permeability loss in hydraulically fractured reservoirs. The experiments involved the reaction of powdered-rock samples with produced brines in batch reactor system at temperature of 95 °C and atmospheric pressure for 7-days and 30-days respectively. Results show changes in mineralogy and chemistry of rock and fluid samples respectively, therefore confirming chemical reactions between the two during the experiments. The mineralogical changes of the rock included decreases of pyrite and feldspar content, whilst carbonate and illite content showed an initial stability and increase respectively before decreasing. Results from analyses of post-reaction fluids generally corroborate the results obtained from mineralogical analyses. Integrating the results obtained from both rocks and fluids reveal a complex trend of reactions between rock and fluid samples which is summarized as follows. Dissolution of pyrite by oxygenated fluid causes transient and localized acidity which triggers the dissolution of feldspar, carbonates, and other minerals susceptible to dissolution under acidic conditions. The dissolution of minerals releases high concentrations of ions, some of which subsequently precipitate secondary minerals. On the field scale, the formation of secondary minerals in the pores and flow paths of hydrocarbons can cause significant reduction in the permeability of the reservoir, which will culminate in rapid productivity decline. This study provides an understanding of the geochemical rock–fluid reactions that impact long term permeability of shale reservoirs.

58 GEOSCIENCES↗
DOE OSTI2022

Plant metacaspase: A case study of microcrystal structure determination and analysis

Metacaspases are highly conserved in plants and play essential roles in mediating programmed cell death, biotic and abiotic stress responses, and damage-induced innate immunity. Ca 2+ signaling induced by plant damage leads to activation of metacaspase from Arabidopsis thaliana (AtMC4), which subsequently processes a plant elicitor peptide to trigger downstream immuno-response. To understand the structural basis of AtMC4 activation by Ca 2+ , we previously determined its crystal structure and performed in-crystal Ca 2+ treatment to probe activation-associated conformational changes. To enable structure determination and in-crystal Ca 2+ activation analysis, we used microcrystals and related methods which were essential for our successful approach. Here, in this paper, we describe in detail the methods that we used for determination of AtMC4 structure using single-wavelength isomorphous replacement with anomalous signals assembled from 22 microcrystals. We also describe the method for in-crystal Ca 2+ soaking, microcrystal data collection, data assembly and analysis to obtain the activated structure of AtMC4 from 91 micro-sized crystals. The described methods may be useful to study other plant metacaspases and more broadly other plant enzymes for their structure determination and in-crystal functional characterization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Revisit the VEC rule in high entropy alloys (HEAs) with high-throughput CALPHAD approach and its applications for material design-A case study with Al–Co–Cr–Fe–Ni system

Valence electron concentration (VEC) was treated as a useful parameter to predict solid solution phases, and the VEC rule was proposed for high entropy alloys (HEAs). However, this empirical rule has its limitations, which restricts its applications for phase predictions in HEAs. In this paper, we revisited the empirical VEC rule with the HT-CALPHAD approach in the Al–Co–Cr–Fe–Ni system. Our investigation showed that more than 90% compositions are observed to have BCC structures when 5.7≤VEC≤7.2 and we got 100% FCC structures when VEC≥8.4. Meanwhile, we proposed a data screening procedure to classify and discover the new HEAs. The concepts of average density (ρHEA), highest BCC/FCC temperatures ($T$ $^{max}_{BCC/FCC}$), and temperature ranges (ΔT BCC/FCC ) were introduced as useful data screening criteria to down-screen the candidate alloy compositions for specific engineering applications. In the current work, we have identified three HEA categories (refractory BCC HEAs, light-weight BCC HEA and refractory FCC HEAs) in the Al–Co–Cr–Fe–Ni system and proposed the best candidate in each group. Here, our investigation showed the HEA non-equiatomic composition space provides ample opportunities for the discovery of the next-generation HEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The influence of cooling rates on strain phase diagrams and domain structures of ferroelectric thin films: A case study of PbTiO 3

Strain engineering has been established as an effective approach to control phase equilibria, domain configurations, and functional properties of ferroelectric thin films. Temperature-strain phase diagrams have been used as powerful tools for providing insights into strain engineering. However, almost all existing phase diagrams established using the phase-field approach assume quenching conditions without considering actual cooling rates during the post-deposition annealing process of ferroelectric thin films. Within this work, we systematically investigate the influence of cooling rates on domain structures and the strain-phase diagram of ferroelectric thin films using phase-field simulations, taking PbTiO 3 thin films as a model system. We found that both the position of phase boundaries in the strain phase diagrams and the domain morphology are significantly influenced by the cooling rates. It is revealed that while the paraelectric-ferroelectric phase boundary remains invariant, the phase boundaries between single-phase and multi-phase regions tend to shift toward the corresponding multi-phase region as the cool rate reduces. Slow cooling generally leads to more ordered domain structures with increased domain size. Using the obtained equilibrium domain structures, we calculated effective thermal conductivities and found significant variations that can be tuned by the cooling rates. In conclusion, this work reveals an underexplored yet critical impact of cooling rates on phase equilibria and domain structures in ferroelectric thin films, which may inspire further fine-tuning of domains and domain walls in low-dimensional ferroelectrics for multifunctional applications.

Domain structures↗
DOE OSTI2026

Tailoring microstructures with mild magnetic-field processing: A case study of CuNiFe alloys

Combined experimental and computational investigations of the CuNiFe spinodal system confirm that application of a mild magnetic field during thermal treatment alters elemental redistribution and the resulting microstructure, relative to that obtained from zero-field annealing. Spinodal decomposition of a Cu 40 Ni 42 Fe 18 alloy was initiated during thermal treatment at 773 K, conducted either under zero field or modest (60 mT) magnetic f ield conditions for up to 200 h. Periodic (~10 nm) chemical modulations into Cu-rich and NiFe-rich regions were observed under both conditions, with the amplitude and wavelength of the segregated regions increasing with treatment time. However, magnetic field annealing resulted in a more than twofold increase in the amplitude of elemental modulations relative to zero-field conditions – consistent with enhanced diffusional f luxes during spinodal decomposition – while the modulation wavelength remained largely unaffected. These microstructural differences are reflected in various extrinsic magnetic properties. In parallel, first-principles DFT calculations indicate that long-range ferromagnetic order, as induced by an applied magnetic field, substantially alters the strength and nature of atomic interactions, enhancing the thermodynamic instability of the CuNiFe solid solution. Collectively, these results suggest that incorporating a mild (millitesla-level) magnetic field – distinct from the strong (tesla-level) fields commonly used in prior studies – during thermal processing has the potential to deliver enhanced control of microstructures for targeted engineering outcomes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bayesian modeling of traffic-related air pollutants: A case study of urban transportation and air quality dynamics in Columbia, South Carolina

Traffic emissions significantly impact near-road air quality and public health. This research applies a Bayesian modeling framework to investigate these impacts using high-resolution traffic and air pollutant data from an urban corridor in Columbia, South Carolina. Despite a data collection period truncated by the COVID-19 lockdown, the Bayesian approach successfully identified significant predictors and quantified model uncertainty. Employing Bayesian Model Selection and Averaging enhanced prediction accuracy and evaluated model uncertainty. Findings indicate that higher temperatures and increased moisture levels elevate particulate matter (PM 1.0 , PM 2.5 , PM 10 ) concentrations, while traffic speed significantly affects nitrogen dioxide (NO 2 ) levels. Specifically, higher average traffic speeds (indicative of smoother flow) correspond to lower NO 2 concentrations, suggesting that less congested conditions reduce NO 2 emissions. This study highlights the robustness of Bayesian methods for generating reliable air quality insights even under data-constrained conditions. The findings underscore the importance of traffic flow management (e.g., reducing congestion) for mitigating near-road NO 2 exposure and provide a basis for developing targeted public health strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Crowded supported metal atoms on catalytically active supports may compromise intrinsic activity: A case study of dual-site Pt/α-MoC catalysts

Increasing the surface population of supported catalytic sites, assuming these sites are stable, is considered a straightforward approach to improving the overall catalytic performance. Here, we report an exception represented by the Pt/α-MoC catalysts featuring atomically dispersed Pt. The Pt/α-MoC catalysts display very high activity for the reverse water gas shift reaction with near 100% CO selectivity for CO 2 :H 2 ratios from 0.25 to 4 and from 250 to 400 °C. Despite the excellent performance, the intrinsic activity per Pt-centric catalytic center declines as the Pt loading increases from 0.1 to 1.0 wt%. With the dispersed Pt evolving from isolated atoms to fully exposed ensembles, the shrinking inter-Pt-atom space impedes CO 2 activation at the critical Pt-Mo interfaces, where the Pt shall temporarily take the -O intermediates. The Pt, even as atomically dispersed without noticeable sintering, is underutilized in such a crowded state. This caution for high-loading catalyst design is translational to other systems where the direct catalytic roles of the supports are crucial.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗