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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 541 records · Page 30

On the competition between mixing rate and uniformity in a coaxial hydrodynamic focusing mixer

Fast microfluidic mixers for use with line-of-sight integrating detection schemes pose unique challenges. Such detectors typically cannot discriminate signal from slow moving (e.g. near internal walls) and fast-moving portions of the fluid stream. This convolves reaction rate dynamics with fluid flow residence time dynamics. Further, the small cross sections of typical three-dimensional hydrodynamic focusing devices lead to lower detection signals. The current study focuses on achieving both small time scales of mixing and homogenous residence times. This is achieved by injecting sample through a center capillary and hydrodynamically focusing using a sheath flow within a tapered second capillary. The current design also features a third, larger coaxial capillary. The mixed stream flows into the large cross-section of this third capillary to decelerate and expand the stream by up to 14-fold to improve line-of-sight signal strength of reaction products. Hydrodynamic focusing, mixing, and expansion are studied using analytical and numerical models and also studied experimentally using a fluorescein-iodide quenching reaction. The experimentally validated models are used to explore trade-offs between mixing rate and uniformity. For the first time, this work presents detailed analysis of the Lagrangian time history of species transport during mixing inside coaxial capillaries to measure mixing nonuniformity. The mixing region enables order 100 μs mixing times and residence time widths of the same order (140 μs).

42 ENGINEERING↗

Chemical trends favoring interstitial cluster formation in bcc high-entropy alloys from first-principles calculations

Achieving high strength and ductility is a common goal in structural alloy design. Body-centered cubic high-entropy alloys (HEAs) commonly highlight the conflict between these properties, with stronger alloys being brittle and vice versa. Recent reports suggest interstitial solutes can be used to overcome this trade-off, in some cases providing both strength and ductility enhancements. This effect has been correlated with interstitial cluster formation, although the conditions favoring their formation remain incompletely understood. Using first-principles calculations of solution energies and diffusivities, we provide insights into thermodynamic and kinetic factors favoring interstitial solute clusters. Among C, N and O solutes, O interstitials display most desirable diffusion kinetics. Further, the results highlight the importance of local composition fluctuations in the HEAs to enable the formation of clusters of appreciable size. The results are explained in terms of bonding and distortion trends across solutes and HEA compositions to provide guidelines for alloy design.

Borges, Pedro P P O↗

Strain-rate hardening enhances fatigue resistance of AlSi10Mg alloy at 350°C

The high cycle fatigue behavior of laser powder bed fusion processed AlSi10Mg has been investigated at 350 °C (T/T m ∼ 0.7). The alloy exhibited a fatigue strength of 30 MPa defined by runout after 10 7 cycles at a conventional loading frequency of 20 Hz, corresponding to a notable fatigue strength to ultimate tensile strength ratio of 0.73. The surprising fatigue resistance was attributed to the strain-rate hardening effect at high fatigue loading frequency relative to tensile loading rates at 350 °C. The strain-rate hardening effect was validated by performing ultrasonic fatigue tests (20 kHz loading frequency) with three orders of magnitude higher strain-rates than those at conventional loading frequency. The higher strain-rates in ultrasonic fatigue increased the magnitude of strain-rate hardening resulting in longer AlSi10Mg fatigue lives compared to fatigue at conventional frequency, thus confirming the strain-rate hardening effect. The fatigue crack initiation mechanism was strain-rate dependent. Post-mortem microstructural examination revealed intergranular cavitation inside clusters of fine equiaxed grains. The cavities interlinked with each other to initiate near-surface fatigue cracks at conventional frequency. Cavitation occurred to a lesser extent at the ultrasonic frequency. As a result, fatigue cracks initiated at pre-existing processing defects near the surface in ultrasonic fatigue samples. Finally, this investigation underscores the role of fine grain clusters in promoting high-temperature fatigue crack initiation and indicates a possible trade-off between printability via grain refinement and high-temperature fatigue resistance of additively manufactured alloys.

Additive manufacturing↗

Economics of electric vehicle corridor fast charging in the United States

Corridor direct-current fast charging (DCFC) stations enable long-distance electric vehicle travel, yet their economics remain uncertain due to high capital costs, low initial utilization, and exposure to utility demand charges. This study evaluates the long-term economics of corridor DCFC across the United States, incorporating capital and operating expenses-including charging equipment and real-world utility tariffs-alongside modeled station utilization, financial incentives, and ancillary retail revenue. In the Baseline scenario, modeled breakeven costs for corridor DCFC average $\$$0.42/kWh over 20 years, yet fewer than half of stations reach cost parity with gasoline on a per-mile basis. Utilization is the primary driver of cost variation, with low-utilization stations costing roughly six times more per kilowatt-hour than the national average. Excluding stations that fail to reach cost parity reduces National Highway System coverage within 50 miles from 94% to 67%, underscoring the trade-off between market-driven deployment and comprehensive network coverage. These results provide guidance for charging providers, utilities, planners, and policymakers seeking to develop and sustain a financially viable national corridor charging network.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Laser powder bed fusion of Inconel 718 on 316 stainless steel

The joining of Inconel 718 and 316 stainless steel has notable industrial importance. However, traditional arc-welding has many issues. In particular, the formation of the detrimental Nb-rich Laves phase in the heat affected zone can promote crack initiation and propagation, which leads to poor mechanical properties. The small heat input and the rapid solidification of laser powder bed fusion (PBF) has the potential to suppress this problem. Despite the infancy of the multi-material PBF, it is of interest to investigate the relationship among the process parameter, the microstructure at the materials joining point, and the mechanical performance. In this study, we used high-speed x-ray imaging to in-situ monitor the printing of Inconel 718 tracks on a 316H SS substrate via laser powder bed fusion, followed by post-build characterization and testing with SEM, XRD and nanoindentation. We observed that a higher linear energy density resulted in a more diffused interface and a smaller compositional gradient, but as a trade-off, generated more keyhole pores and thermal cracks. Furthermore, we also showed that the built layer exhibited chemical inhomogeneity at two length scales: a tens-of-mu m-scale compositional vortex due to the melt flow, and a sub-mu m-scale Nb-rich dendritic structure due to the non-equilibrium solidification that led to the formation of the Laves phase. It was inferred that the chemical inhomogeneity may benefit the mechanical properties at the interface by providing more interlocking between the two materials and also by limiting the effect of the brittle Laves phase to potentially short range.

36 MATERIALS SCIENCE↗

Volatile organic compound emissions from 4D printing: Effects of material composition and external stimulus

4D printing of stimuli-responsive materials extends 3D printing by enabling the fabricated structures to transform their shapes and properties over time in response to external stimuli. Numerous research efforts have been dedicated to developing new smart materials, enhancing material printability, and ensuring time-evolving properties. Meanwhile, the use of smart materials and external stimuli in 4D printing has introduced the possibility of air emissions that can potentially deteriorate the indoor air quality at the workplace and pose continuous health hazards to users during the production and use phases. These potential air emissions caused by 4D printing have not yet been assessed in current literature, leading to unknown occupational hazards and human health effects. This study focuses on stereolithography-based 4D printing with constrained thermo-mechanics and builds an emission model to quantify the volatile organic compound emissions from printing, shape programming, and shape recovery stages. The established model mathematically links the emission characteristics with material compositional design and stimuli-response mechanisms. Additionally, shape fixity and recovery abilities are considered to analyze the trade-off between the air emissions and stimuli-response performance of 4D printed parts. Case study results suggest that the methacrylate-based thermo-responsive material with higher glass transition temperature leads to higher air emissions, surpassing the permissible exposure level in the indoor environment. By altering the thermo-temporal conditions, a 61.29% reduction in emission yield can be achieved while ensuring a satisfactory shape memory performance.

36 MATERIALS SCIENCE↗

Aggregation in bottom-up vulnerability assessments and equity implications: The case of Jordanian households’ water supply

Bottom-up methods for water resources modeling rely on acceptability thresholds to find, through a response surface, which deeply uncertain futures lead to system failure. They commonly treat water users as aggregate actors, which may preclude analysis of the equity impacts of interventions. This paper explores how aggregation choices for large groups of water users lead to different policy recommendations in response surface assessments. Herein, two aggregation methods with varying parameters are considered: percentile satisfaction targets and generalized mean. A 2-dimensional stress-test assessment across groundwater availability and population is applied to household water supply in Jordan. The study compares six different policies covering supply enhancement and rebalancing, using a country-wide multi-agent model that characterizes households across socioeconomic strata. For different aggregation levels, policies are ordered by their associated robustness index. Results show that aggregation choices may modify response surfaces as much as policy changes and strongly determine policy preference. Modifying allocation rules can substantially reduce the disparity in household vulnerability. Preferences defined by aggregation intervals provide a finer understanding of trade-offs among water users and may improve deliberation over equity under deep uncertainty.

54 ENVIRONMENTAL SCIENCES↗

Warming but not elevated CO 2 depletes soil organic carbon in a temperate rice paddy

In this article, global climate change has the potential to alter soil organic carbon (SOC) stocks in rice paddies, because increases in temperature and atmospheric carbon dioxide concentration ([CO 2 ]) both influence the primary input (i.e., net primary production, NPP) and output (i.e. heterotrophic respiration) of carbon (C). We used two types of open-top chambers representing present conditions (+0°C, +0 ppm CO 2 ) and projected climate change conditions (+2°C, +200 ppm CO 2 ) to investigate the net effect of climate change on SOC stock in rice paddy. Additional chambers with elevated temperature only (+2°C, +0 ppm CO 2 ) allowed us to quantify the individual effects of temperature and [CO 2 ]. We calculated changes in SOC stock using net ecosystem C balance (NECB) analysis (i.e., the balance between C inputs and outputs). Compared to present conditions, projected climate change did not change grain yield due to a trade-off between the effects of warming and [CO 2 ] on grain yield components. NPP during the fallow season significantly decreased under combined warming and CO 2 , as the impact of warming outweighed that of elevated [CO 2 ]. However, rice NPP remained unchanged during the cropping season. Warming plus elevated CO 2 increased SOC mineralization by 157–429 %, particularly through warming-induced soil CO 2 emission during the fallow season. Consequently, climate change conditions decreased (119–271 %) NECB values compared to present conditions, primarily through the response to warming. Our findings demonstrate that rice paddies represent positive feedback on climate change, because accelerated C release from warmed soils will override C gains from NPP under elevated CO 2 . Reducing SOC depletion in rice paddy agriculture under a changing climate therefore requires conservative soil management practices during the fallow season.

54 ENVIRONMENTAL SCIENCES↗

Matching high resolution satellite data and flux tower footprints improves their agreement in photosynthesis estimates

Mapping canopy photosynthesis in both high spatial and temporal resolution is essential for carbon cycle monitoring in heterogeneous areas. However, well established satellites in sun-synchronous orbits such as Sentinel-2, Landsat and MODIS can only provide either high spatial or high temporal resolution but not both. Recently established CubeSat satellite constellations have created an opportunity to overcome this resolution trade-off. In particular, Planet Fusion allows full utilization of the CubeSat data resolution and coverage while maintaining high radiometric quality. In this study, we used the Planet Fusion surface reflectance product to calculate daily, 3-m resolution, gap-free maps of the near-infrared radiation reflected from vegetation (NIRvP). We then evaluated the performance of these NIRvP maps for estimating canopy photosynthesis by comparing with data from a flux tower network in Sacramento-San Joaquin Delta, California, USA. Overall, NIRvP maps captured temporal variations in canopy photosynthesis of individual sites, despite changes in water extent in the wetlands and frequent mowing in the crop fields. When combining data from all sites, however, we found that robust agreement between NIRvP maps and canopy photosynthesis could only be achieved when matching NIRvP maps to the flux tower footprints. In this case of matched footprints, NIRvP maps showed considerably better performance than in situ NIRvP in estimating canopy photosynthesis both for daily sum and data around the time of satellite overpass (R2 = 0.78 vs. 0.60, for maps vs. in situ for the satellite overpass time case). This difference in performance was mostly due to the higher degree of consistency in slopes of NIRvP-canopy photosynthesis relationships across the study sites for flux tower footprint-matched maps. Our results show the importance of matching satellite observations to the flux tower footprint and demonstrate the potential of CubeSat constellation imagery to monitor canopy photosynthesis remotely at high spatio-temporal resolution.

54 ENVIRONMENTAL SCIENCES↗

Multi-level impacts of climate change and supply disruption events on a potato supply chain: An agent-based modeling approach

Context: The world is experiencing frequent extreme weather events like droughts, snowstorms, and shifting of seasons due to climate change. Increased frequency and severity of these extreme weather events threaten food security because agriculture depends on climate conditions. Impacts of climate change on the agricultural system not only occur at the grower’s level, but also cascade to other levels along the supply chain. Objective: In this study, we aim to quantify a wide range of economic impacts of different extreme climate events on different stages of a food supply chain. Methods: We chose the potato supply chain in Idaho as a case study. We developed a multi-echelon supply chain simulation model using an agent-based modeling (ABM) approach with five types of agents—farmers, shippers, processors, retailers, and logistics companies. In addition to the business-as-usual (BAU) scenario, we designed two climate-related disruption events—drought and snowstorm. We quantified the heterogeneous impacts at different stages of the supply chain for both fresh and processed potatoes using key performance indicators (KPIs) including revenues, prices, lead times, traded quantities, and food waste quantity. Results and Conclusion: The impacts of the disruption events are different on different agents in the supply chain for different product categories. The price hike of fresh potatoes is far higher than processed potatoes during disruption events. This price hike makes consumers switch to processed potatoes, which require more fresh potatoes as an input that further reinforces the price hike. However, because processed potatoes have an elastic demand, once their prices go up due to higher input cost, their demand drops. Non-contracted farmers gain additional revenues from the disruption events, whereas contracted farmers incur a loss due to lock-in price and lower than usual harvest. Significance: The methodology developed in this study could be applied to other food and agricultural supply chains for understanding the vulnerabilities at agent levels due to climate change disruption events. Furthermore, the findings would help develop mitigation strategies or policies to improve the well-being of the overall supply chain.

54 ENVIRONMENTAL SCIENCES↗

Explainable machine learning to quantify the value of proximal remote sensing in latent energy flux estimation

Proximal remote sensing has the potential to provide critical information on vegetation biophysical factors that can predict land-atmosphere exchange of water and energy. Latent energy (LE) flux is traditionally estimated using process-based models which rely on vegetation parameters that change during the growing season. Data-driven models have the potential to address these issues by offering flexible predictor selection and more efficient utilization of the information in predictor sets. These models require careful choice of predictors to avoid redundancy and allow robust cross-validation. In this study we present a systematic and comprehensive evaluation of machine learning (ML) models to assess the capability of meteorological and proximal sensing data for predicting LE at a half-hourly temporal resolution across multiple growing seasons for an agricultural system. The results presented here demonstrate that a model using four environmental predictors in combination with two proximal sensing variables can capture 88 % of the variability in LE. ML models using only three predictors (one meteorological and two proximal remote sensing) captured 81 % of LE variability, offering the best trade-off between performance and complexity. An ML model utilizing only two predictors, one proximal remote sensing variable and downwelling radiation, captured 77 % of LE variability. These results demonstrate the power of proximal remote sensing and meteorological observations to estimate land-atmosphere water vapor exchange, providing a solution where more direct methods such as eddy covariance are not available and for evaluations of agronomic management and genotypic variations.

60 APPLIED LIFE SCIENCES↗

A new algae technical standards focus group: Summarizing and guiding the algae state of the art

The value proposition of algae technical metrics was the subject of a recent, industry-led, Focus Group interactive discussion. The interactive platform allowed for real time capturing and priority ranking of the topics that are deemed critical challenges for a future successful algae-based bioeconomy. This work ultimately sets the stage for providing guidance, methods, and standard reference materials tailored to respective algae industry segments for the cultivation, processing and marketing of high-quality and safe algae-based products. The group solicits input from the broader algae community on the value proposition and presents a case here to build a consensus around algae-specific metrics. The value proposition of technical standards to the industry is that guidance obtained through these collaborations builds producers' and consumers' trust that algae and algae-derived products are safe, reliable, and may allow for expanded market access, and increased competitiveness and international trade.

59 BASIC BIOLOGICAL SCIENCES↗

Peer-to-Peer Energy Systems for Connected Communities: A Review of Recent Advances and Emerging Challenges

After a century of relative stability of the electricity industry, extensive deployment of distributed energy resources and recent advances in computation and communication technologies have changed the nature of how we consume, trade, and apply energy. The power system is facing a transition from its traditional hierarchical structure to a more deregulated model by introducing new energy distribution models such as peer-to- peer (P2P) sharing for connected communities. The proven effectiveness of P2P sharing in benefiting both prosumers and the grid has been demonstrated in many studies and pilot projects. However, there is still no extensive implementation of such sharing models in today’s electricity markets. This paper aims to shed some light on this gap through a comprehensive overview of recent advances in the P2P energy system and an insightful discussion of the challenges that need to be addressed in order to establish P2P sharing as a viable energy management option in today’s electricity market. To this end, in this article, we provide some background on different aspects of P2P sharing. Then, we discuss advances in P2P sharing through a systematic domain-based classification. We also review different pilot projects on P2P sharing across the globe. Finally, we identify and discuss a number of challenges that need to be addressed for scaling up P2P sharing in the electricity market followed by concluding remarks at the end of the paper.

Tushar, Wayes↗

Dynamic Linking of Upstream Energy and Freight Demands for Bio and Fossil Energy Pathways in the Global Change Analysis Model

Comprehensive study of the environmental impacts associated with demand for an energy resource or carrier in any one sector requires a full consideration of the direct and indirect impacts on the rest of the regional and global energy system. It is important to consider the energy that is consumed in producing primary energy resources and energy consumed in transporting these energy resources internationally and domestically in order to produce a complete picture of these impacts. Biofuels are especially complex since they have feedbacks not just to the energy system but also to regional and global crop markets. Different modeling and analysis strategies have been applied to consider these impacts, which occur “upstream” of final energy consumption, with some success. Traditional life cycle models allow for rich technological detail in linking upstream impacts of energy demand with downstream final consumption; however, they cannot by themselves represent dynamic economic feedbacks across multiple sectors and regions over time. Computable general equilibrium (CGE) modeling does account for economic feedback among all sectors and regions; however, CGE modeling does not lend itself to physical representation of technological detail. Partial equilibrium (PE) modeling is a heterogeneous category describing economic models that focus on a subset of the economy, and they differ in coverage and ease in incorporating more sectors and economic links. In this study, we present a strategy for dynamically including the direct and indirect impacts of energy demand with physical and technology detail by explicitly adding these upstream energy and transportation links to GCAM, a PE model of global energy, land use, and emissions. We incorporate the following inter-sectoral linkages: energy inputs to crop production, energy inputs to fossil resource production, and freight transport requirements of energy and agricultural commodities. We assess the implications of explicitly including these links by measuring the global impacts of increased corn ethanol demand in the United States with and without these links included. Although the net global impact of the upstream links on energy and emissions are relatively modest in the scenarios we studied, the inclusion of these links illustrates interesting trade-offs in energy and transportation demand among fossil fuel and agriculture sectors. These sectoral interactions suggest that this level of modeling detail could be important in evaluating future analytical questions.

Sampedro Martinez de Estivariz, Jon↗

Energy and power quality measurement for electrical distribution in AC and DC microgrid buildings

Today's selection of DC microgrid buildings features a diverse set of electrical topologies and turnkey solutions, each with specific design trade-offs and optimizations. Designers desperately need standardized metrics and procedures for measurement and verification (M&V) to analyze and compare the advantages of each DC solution to traditional AC building networks. This work develops M&V procedures for quantifying and comparing the energy efficiency and power quality in buildings. To calculate full-building efficiency, this work introduces the measurement-informed modeling method, a procedure that develops and refines a building's energy model with metered data. To quantify power quality, this work defines a new voltage quality index that applies to both AC and DC buildings. This article describes the equipment, instrumentation, and operation necessary to calculate the efficiency and power quality. It then demonstrates these methods with a set of field tests. We report these M&V procedures can ultimately be used to compare and improve the efficiency and power quality of various DC topologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Decarbonization scenarios of the U.S. Electricity system and their costs

Decarbonizing the electricity system to zero-carbon emission is crucial for climate change mitigation. Previous studies have shown that such a transition in the United States (U.S.) may lead to higher system cost compared to a business-as-usual case, but it is not well-known how the cost of electricity generation varies at sub-regional level under the transition, and studies have rarely evaluated the trade-off between the cost and avoided climate damages, as well as the potential roles of negative emission technologies (NETs) in the electricity decarbonization. In this work, we present a regionally resolved national model to quantify the cost of decarbonizing the U.S. electricity system under a set of possible scenarios. The results show that, compared to the reference scenario without a decarbonization policy, reaching zero CO 2 emission by 2050 would incur, depending on the scenarios, 335-494 billion USD additional cost to the U.S. electric power sector during 2020-2050. The regional costs of electricity generation ranges from 2.4 to 4.7 cent/kWh, largely due to the generation profiles and renewable resources availability of those regions. The additional costs can be translated to an average CO 2 abatement cost of 29-59 USD/metric ton CO 2 (with 2%-7% discount rates), which are comparable to the social cost of carbon in the literature at around 4% discount rate. The results also show that the cost of mitigating the last few percent CO 2 emission from the U.S. electricity system may exceed the costs of NETs, indicating an opportunity for NETs to contribute to electricity decarbonization.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Low-cost crushed-rock heat storage with oil or salt heat transfer

The demand for variable electricity and heat is met by fossil-fuel power plants because the power plant capital costs and the cost of storing fossil fuels are low. A low-carbon economy requires replacement of the storage function of fossil fuels to provide variable heat and electricity as needed. The Crushed Rock Ultra-large Stored Heat (CRUSH) system is a new technology with the goal to provide heat storage at an incremental capital cost of $2–4/kWh at scales of 10 s to 100 s of GWhs that enables economic daily to multi-week storage. CRUSH can be coupled to nuclear power plants, concentrated solar power (CSP) plants and thermal energy batteries to provide variable electricity and heat on demand. Sensible heat is stored in crushed rock—the lowest-cost heat-storage material. Heat is transferred to and from the crushed rock using nitrate salt or heat-transfer oils but these fluids do not store heat. Heat from a nuclear reactor, CSP plant or conversion of low-price electricity into heat is used to heat the salt or oil. The hot fluid is poured over the crushed rock, trickles downward by gravity through the rock, heats the rock and is collected by the drain pans under the crushed rock. To recover heat cold salt or oil is poured over hot crushed rock, trickles down by gravity while being heated and is collected by the drain pans under the crushed rock. The system design and engineering trade-offs are described. The technology is in the early stages of development.

20 FOSSIL-FUELED POWER PLANTS↗