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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 217 records · Page 12

Experimental validation of multiphysics model simulations of the thermal response of a cement clinker rotary kiln at laboratory scale

Abstract An increasing demand for buildings, transportation systems and civil infrastructure development has driven expansion of cement consumption world‐wide, producing a significant increase in related global energy demand. With approximately 7% of the world‐wide industrial energy consumption (10.7 exajoules [EJ]), the cement industry is the third most energy intensive industrial processes and a key component for concrete, the most consumed composite material in the global construction industry. In cement manufacturing, the cement kiln accounts for most of the energy consumption in the production process. As the heart of a cement plant, the cement kiln is where the kiln feed primarily containing calcium oxide (CaO), silica (SiO 2 ), alumina (Al 2 O 3 ), and iron (Fe 2 O 3 ) are thermally and chemically transformed into clinker minerals. The presented work developed a multiphysics model, designed and built a laboratory‐scale rotary cement clinker kiln, and produced cement clinker at laboratory‐scale. The model was developed to study the interaction between the various thermal, fluid dynamic and chemical interactions involved in the sintering process used to form Portland cement clinker in an effort to reduce energy use. The analytical model was validated through experimental testing using a unique laboratory‐scale rotary cement kiln developed during the investigation. Also demonstrated was the feasibility of producing clinker at laboratory scale. This modeling and lab scale tests were designed to better understand the clinker sintering process so that operational and quality decisions can be made to optimize energy consumption without compromising cement clinker quality. The computational fluid dynamics modeling was developed in COMSOL Multiphysics 6.0. The characteristics of the combustion fluid flow, concentration of species, temperature and heat transfer were studied for a turbulent flow of methane (CH 4 ) gas and oxygen (O 2 ). Theory suggests that heat transfer impacts the cement production process but the multiphysics model more accurately describes the convection, conduction, and radiant heat transfer in the kilning process and thus allows for a better understanding of the energy exchange driving the chemical reactions that produce Portland cement. Clinker minerals were formed because of appropriate burning conditions implemented during experimental model validation.

Tabares, Juan David↗

Real-time control of connected vehicles in signalized corridors using pseudospectral convex optimization

Recent advances in Connected and Automated Vehicle (CAV) technologies have opened up new opportunities to enable safe, efficient, and sustainable transportation systems. However, developing reliable and rapid speed control algorithms in highly dynamic environments with complex inter-vehicle interactions and nonlinear vehicle dynamics is still a daunting task. In this paper, we develop a novel speed control method for CAVs to produce optimal speed profiles that minimize the fuel consumption and avoid idling at signalized intersections. To this end, an optimal control problem is formulated using the information of the upcoming traffic signal to adapt vehicles' speeds to avoid frequent stop-and-go driving patterns. Here, by applying the pseudospectral discretization method and the sequential convex programming method, the computational efficiency is greatly improved, enabling potential real-time on-vehicle applications. In addition, the algorithm is implemented under a model predictive control framework to ensure online control with instant response for collision avoidance and robust vehicle coordination. The proposed algorithm is verified through numerical simulations of three different traffic scenarios. The convergence and accuracy of the proposed approach are demonstrated by comparing with a popular nonlinear solver. Furthermore, the benefit of the proposed method in both traffic mobility and fuel efficiency is validated using the speed profile determined from a traffic following model in a simulation software as the baseline.

42 ENGINEERING↗

Crystal structure of Campylobacter jejuni lipoprotein Cj1090c

In Gram-negative bacteria, lipopolysaccharide (LPS) is an essential component of the asymmetric outer membrane (OM). LptE is an OM lipoprotein that forms a complex with the β-barrel OM protein, LptD. Incorporation of LPS into the OM outer leaflet is essential for bacterial viability, and mediated by the LptD/E complex. The genome of Campylobacter jejuni, a major foodborne pathogen, contains over 20 putative lipoproteins including Cj1090c. Here, we report the crystal structure of Cj1090c at 2.4 Å resolution, revealing structural evidence for LptE in C. jejuni. The analysis of this crystal structure, along with the genomic context, allows us to propose the C. jejuni LPS transport system for the first time, and also permits for discussion of the features of the LptD/E complex of C. jejuni.

59 BASIC BIOLOGICAL SCIENCES↗

Impact of cyberattacks on safety and stability of connected and automated vehicle platoons under lane changes

Connected and automated vehicles (CAVs) offer a huge potential to improve the operations and safety of transportation systems. However, the use of smart devices and communications in CAVs introduce new risks. CAVs would leverage vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication, thus providing additional system access points compared to traditional systems. Automation makes these systems more vulnerable and increases the consequences of cyberattacks. This study utilizes an infrastructure-based communication platform consisting of cooperative adaptive cruise control and lane control advisories developed by the authors to perform cyber risk assessment of CAVs. The study emulates three types of cyberattacks (message falsification, dedicated denial of service, and spoofing attacks) in a representative traffic environment consisting of multiple CAV platoons and lane change events to analyze the safety and stability impacts of the cyberattacks. Simulation experiments using VISSIM reveals that traffic stream and CAV string is unstable under all three types of cyberattacks. The worst case is represented by the message falsification attack. Increases in volatility are observed over a no attack case, with variations increasing by an average of 43%–51% along with an increase of over 3000 crash conflicts. Similarly, lane change crash conflicts are observed to be more severe compared to rear end crash conflicts, showing a higher probability of severe injuries. Further, the case of slight cyberattack on a single CAV also creates significant disruption in the traffic stream. Analysis of variance (ANOVA) reveals the statistical significance of the results. Furthermore, these results pave the way for future design of secure systems from a monitoring perspective.

97 MATHEMATICS AND COMPUTING↗

Biomass supply chain equipment for renewable fuels production: A review

The production of renewable fuels is a critical component of global strategies to reduce greenhouse gas (GHG) emissions. Moreover, the collection of raw materials for its production can provide added benefits such as reduction of wildfire risk, additional income for farmers, and decreased disposal costs. Although there is substantial literature on design and modeling of supply chains, the authors were unable to find a single reference with the information needed for the selection and cost estimation of each type of equipment involved in the supply chain. Therefore, the goal of this research is to gather information necessary for the construction and utilization of models that might drive the identification of a feasible supply chain to produce renewable fuels at a commercial scale. The primary objectives are to 1) understand the supply chain of critical feedstocks for renewable fuels production; 2) identify the equipment commercially available for collection and adequation of feedstock; and 3) consolidate information regarding equipment cost, energy consumption, and efficiency, as well as feedstock storage and transportation systems. This paper provides a compilation for five feedstock types studied for sustainable aviation fuel production: 1) agricultural residues and grasses, 2) forest residues, 3) urban wood waste, 4) oilseeds, 5) fats, oils & greases. All the technologies involved from the field to the gate of the preprocessing or conversion unit were reviewed. The information on fats, oils & greases supply chains and equipment purposely designed for forest thinning and pruning was very limited.

: Feedstock, Collection and Adequation, Renewable ↗

Spatiotemporal features of traffic help reduce automatic accident detection time

Quick and reliable automatic detection of traffic accidents is of paramount importance to save human lives in transportation systems. However, automatically detecting when accidents occur has proven challenging, and minimizing the time to detect accidents (TTDA) by using traditional features in machine learning (ML) classifiers has plateaued. We hypothesize that accidents affect traffic farther from the accident location than previously reported. Therefore, leveraging traffic signatures from neighboring sensors that are adjacent to accidents should help improve their detection. We confirm this hypothesis by using verified ground-truth accident data, traffic data from radar detection system sensors, and light and weather conditions and show that we can minimize the TTDA while maximizing classification performance by considering spatiotemporal features of traffic. Specifically, we compare the performance of different ML classifiers (i.e, logistic regression, random forest, and XGBoost) when controlling for different numbers of neighboring sensors and TTDA horizons. We use data from interstates 75 and 24 in the metropolitan area that surrounds Chattanooga, TN. Our results show that the XGBoost classifier produces the best results by detecting accidents as quickly as 1.0 min after their occurrence with an area under the receiver operating characteristic curve of up to 83% and an average precision of up to 49%. We describe limitations, open challenges, and how the proposed framework can be used for quicker operational accident detection.

33 ADVANCED PROPULSION SYSTEMS↗

Ecological theory applied to environmental metabolomes reveals compositional divergence despite conserved molecular properties

Stream and river systems transport and process substantial amounts of dissolved organic matter (DOM) from terrestrial and aquatic sources to the ocean, with global biogeochemical implications. However, the underlying mechanisms affecting the spatiotemporal organization of DOM composition are under-investigated. To understand the principles governing DOM composition, we leverage the recently proposed synthesis of metacommunity ecology and metabolomics, termed ‘meta-metabolome ecology.’ Applying this novel approach to a freshwater ecosystem, we demonstrated that despite similar molecular properties across metabolomes, metabolite identity significantly diverged due to environmental filtering and variations in putative biochemical transformations. We refer to this phenomenon as ‘thermodynamic redundancy,’ which is analogous to the ecological concept of functional redundancy. We suggest that under thermodynamic redundancy, divergent metabolomes can support equivalent biogeochemical function just as divergent ecological communities can support equivalent ecosystem function. As these analyses are performed in additional ecosystems, potentially generalizable principles, like thermodynamic redundancy, can be revealed and provide insight into DOM dynamics.

Danczak, Robert E.↗

Multiscale geographically and temporally weighted regression (MGTWR): exploring the spatiotemporal heterogeneity of EV market adoption

As an innovative vehicle technology, electric vehicles are experiencing growing sales and have made significant inroads into the traditional automotive market in the United States and around the world. However, EV adoption rates vary significantly across space and over time, influenced by a complex interplay of socio-economic and infrastructural factors alongside federal and state policies. Here, this paper presents a comprehensive spatial–temporal investigation of EV market adoption within one city in the US, that of Chicago, utilizing Multiscale Geographically and Temporally Weighted Regression (MGTWR) alongside Multiscale Geographically Weighted Regression (MGWR). The aim is to unravel the spatial and temporal dynamics affecting EV adoption and to explore how the influence of various determinants of EV adoption, such as demographic factors and economic conditions, vary spatially. Moreover, by utilizing MGTWR, we provide insights into the evolution of these relationships over time, offering a predictive outlook on future EV market growth. Our findings, with an 86.6% prediction accuracy for EV market adoption, tailored policy measures to support accelerated EV adoption. Methodologically, this work advances MGWR frameworks by integrating temporal dynamics to examine nonstationary processes in spatially disaggregated contexts. These findings offer evidence–based guidance for policymakers, urban planners, and stakeholders in the automotive industry, supporting the transition toward a more sustainable and efficient transportation system.

EV Market Adoption↗

A framework for integrated dispatching and charging management of an autonomous electric vehicle ride-hailing fleet

The convergence of electrification and automated driving will introduce opportunities to improve the operation and energy-efficiency of transportation systems. This paper discusses the challenges of dispatching autonomous electric vehicles (AEVs) in a ride-hailing fleet and their interactions with charging infrastructure. An integrated decision-making framework for dispatching and charging has been proposed using system optimization approaches. An agent-based platform has been developed for simulating and testing the proposed methods. A case study using New York City taxi data has been performed with different fleet sizes, dispatching strategies, and charging networks. Advantages of optimization-based approaches for AEV fleet management have been studied and demonstrated, for example, for a fleet of 1,750 AEVs to meet 100,000 daily requests, optimization-based centralized fleet management would result in 14% more ride requests satisfied and 43% fewer zero-occupancy miles traveled than if AEVs make independent decisions based on heuristic strategy. Benefits on reducing fleet size and charging downtime from optimization approaches are also comprehensively illustrated.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hybrid biological-chemical strategy for converting polyethylene into a recyclable plastic monomer using engineered Corynebacterium glutamicum

Converting polyethylene (PE) into valuable materials, particularly ones that are better for the environment than the incumbent plastics, not only helps mitigate environmental issues caused by plastic waste but also alleviates the long-standing problem of microbial fermentation competing with food supplies. However, the inherent robustness of PE due to its strong carbon-carbon bonds and high molecular weight necessitates harsh decomposition conditions, resulting in diverse decomposition outcomes that present significant challenges for downstream applications, especially for bioconversion. In this study, we demonstrate a hybrid biological-chemical conversion process for PE, converting its decomposition products, namely short-chain diacids, into a monomer, β-keto-δ-lactone (BKDL), for highly recyclable polydiketoenimine plastics using engineered Corynebacterium glutamicum. Since BKDL synthesis requires a substantial supply of malonyl-CoA, we employed an alternative biosynthesis pathway that leverages C. glutamicum's natural proficiency in amino acid production. We optimized this pathway in vivo by minimizing carbon loss to CO2 and byproducts, improving the transporter system, and maximizing co-factor regeneration. Furthermore, we co-optimized the PE deconstruction process to produce predominantly C4 to C6 diacids and integrated three catabolic pathways into the engineered strain to enhance diacid utilization, maximizing the carbon conversion from PE. Finally, an engineered polyketide synthase was introduced into C. glutamicum to enable BKDL synthesis. This work demonstrates the potential of a chemo-biological hybrid strategy for recycling plastic waste, highlighting its promise in addressing environmental challenges and promoting sustainable materials.

Zhan, Chunjun↗

Numerical Analysis of Offshore Wind-Farm-Induced Drag Effects on Coastal Upwelling Dynamics

Wind farms extract momentum from the atmospheric flow, generating wind-speed deficits both within the plant, and extending downstream. When located offshore, these deficits modulate air-sea coupling, potentially impacting coastal upwelling in sensitive regions. We investigate impacts of wind farms on coastal upwelling using kilometre-scale, three-way-coupled simulations with the coupled ocean-atmosphere-wave-sediment transport system for the US West Coast. Wind-farm effects are represented by a generalised turbine drag formulation, an idealised, height-dependent body force whose magnitude is systematically varied. This approach isolates the leading-order fluid-dynamical response in a realistic coastal configuration. The atmospheric adjustment exhibits an approximately linear relation between drag force and wind-speed deficit, with wakes that expand downstream and increase in magnitude as drag increases. An empirical orthogonal function analysis of sea-surface-temperature anomalies reveals the emergence of a canonical dipole pattern under strong drag forcing. Subsurface diagnostics show consistent shoaling of the mixed layer and suppressed upward velocities in areas near wind-farm region, accompanied by compensating enhancements of shoaling closer to the coast. These results identify turbine drag as a control parameter in assessing interactions between wind-farm wake and coastal upwelling and provide scaling relationships for understanding offshore wind-farm effects on the coastal circulation dynamics.

16 TIDAL AND WAVE POWER↗

Generation of Pseudomonas putida KT2440 Strains with Efficient Utilization of Xylose and Galactose via Adaptive Laboratory Evolution

While Pseudomonas putida KT2440 has great potential for biomass-converting processes, its inability to utilize the biomass abundant sugars xylose and galactose has limited its applications. Here, in this study, we utilized Adaptive Laboratory Evolution (ALE) to optimize engineered KT2440 with heterologous expression of xylD encoding xylonate dehydratase from Caulobacter crescentus and galETKM encoding UDP-glucose 4-epimerase, galactose-1-phosphate uridylyltransferase, galactokinase, and galactose-1-epimerase from Escherichia coli K-12 MG1655. Poor starting strain growth (<0.1 h –1 or none) was evolutionarily optimized to rates of up to 0.25 h –1 on xylose and 0.52 h –1 on galactose. Whole-genome sequencing, transcriptomic analysis, and growth screens revealed significant roles of kguT encoding a 2-ketogluconate operon repressor and 2-ketogluconate transporter, and gtsABCD encoding an ATP-binding cassette (ABC) sugar transporting system in xylose and galactose growth conditions, respectively. Finally, we expressed the heterologous indigoidine production pathway in the evolved and unevolved engineered strains and successfully produced 3.2 g/L and 2.2 g/L from 10 g/L of either xylose or galactose in the evolved strains whereas the unevolved strains did not produce any detectable product. Thus, the generated KT2440 strains have the potential for broad application as optimized platform chassis to develop efficient microorganism-based biomass-utilizing bioprocesses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An essential role for tungsten in the ecology and evolution of a previously uncultivated lineage of anaerobic, thermophilic Archaea

Trace metals have been an important ingredient for life throughout Earth’s history. Here, we describe the genome-guided cultivation of a member of the elusive archaeal lineage Caldarchaeales (syn. Aigarchaeota), Wolframiiraptor gerlachensis, and its growth dependence on tungsten. A metagenome-assembled genome (MAG) of W. gerlachensis encodes putative tungsten membrane transport systems, as well as pathways for anaerobic oxidation of sugars probably mediated by tungsten-dependent ferredoxin oxidoreductases that are expressed during growth. Catalyzed reporter deposition-fluorescence in-situ hybridization (CARD-FISH) and nanoscale secondary ion mass spectrometry (nanoSIMS) show that W. gerlachensis preferentially assimilates xylose. Phylogenetic analyses of 78 high-quality Wolframiiraptoraceae MAGs from terrestrial and marine hydrothermal systems suggest that tungsten-associated enzymes were present in the last common ancestor of extant Wolframiiraptoraceae. Our observations imply a crucial role for tungsten-dependent metabolism in the origin and evolution of this lineage, and hint at a relic metabolic dependence on this trace metal in early anaerobic thermophiles.

59 BASIC BIOLOGICAL SCIENCES↗

Unnatural biosynthesis by an engineered microorganism with heterologously expressed natural enzymes and an artificial metalloenzyme

Synthetic biology enables microbial hosts to produce complex molecules from organisms that are rare or difficult to cultivate, but the structures of these molecules are limited to those formed by reactions of natural enzymes. The integration of artificial metalloenzymes (ArMs) that catalyse unnatural reactions into metabolic networks could broaden the cache of molecules produced biosynthetically. Here, in this work, we report an engineered microbial cell expressing a heterologous biosynthetic pathway, containing both natural enzymes and ArMs, that produces an unnatural product with high diastereoselectivity. We engineered Escherichia coli with a heterologous terpene biosynthetic pathway and an ArM containing an iridium–porphyrin complex that was transported into the cell with a heterologous transport system. We improved the diastereoselectivity and product titre of the unnatural product by evolving the ArM and selecting the appropriate gene induction and cultivation conditions. This work shows that synthetic biology and synthetic chemistry can produce, by combining natural and artificial enzymes in whole cells, molecules that were previously inaccessible to nature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hall effect in gated single-wall carbon nanotube films

The presence of hopping carriers and grain boundaries can sometimes lead to anomalous carrier types and density overestimation in Hall-effect measurements. Previous Hall-effect studies on carbon nanotube films reported unreasonably large carrier densities without independent assessments of the carrier types and densities. Here, we have systematically investigated the validity of Hall-effect results for a series of metallic, semiconducting, and metal–semiconductor-mixed single-wall carbon nanotube films. With carrier densities controlled through applied gate voltages, we were able to observe the Hall effect both in the n- and p-type regions, detecting opposite signs in the Hall coefficient. By comparing the obtained carrier types and densities against values derived from simultaneous field-effect-transistor measurements, we found that, while the Hall carrier types were always correct, the Hall carrier densities were overestimated by up to four orders of magnitude. This significant overestimation indicates that thin films of one-dimensional SWCNTs are quite different from conventional hopping transport systems.

42 ENGINEERING↗

Electrification pathways for U.S. passenger vehicles

As electric vehicle (EV) adoption continues to accelerate, we explore the implications of different adoption trajectories that achieve a full transition to EVs by 2050 for U.S. light-duty passenger vehicles (LDVs). Using a vetted transportation system model, we find that achieving 100% EV sales by 2040 would decrease tailpipe greenhouse gases (GHGs) by 90% between 2022 and 2050, leaving about 45 million gasoline vehicles on the road. Achieving 100% sales by 2035, tailpipe emissions decrease 93%, with about 28 million gasoline vehicles on the road in 2050 (9% of stock). Slower EV adoption, reaching 100% sales by 2045, would result in 69 million gasoline vehicles on the road in 2050. Fully electrifying passenger vehicles by 2050 would require a full transition to EVs sales in the 2030s coupled with either changes to mobility, or an accelerated stock turnover in the 2040s with additional 19–30% annual LDV sales.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Potential-induced wetting and dewetting in pH-responsive block copolymer membranes for mass transport control

Wetting and dewetting behavior in channel-confined hydrophobic volumes is used in biological membranes to effect selective ion/molecular transport. Artificial biomimetic hydrophobic nanopores have been devised utilizing wetting and dewetting, however, tunable mass transport control utilizing multiple transport modes is required for applications such as controllable release/transport, water separation/purification and energy conversion. Here, we investigate the potential-induced wetting and dewetting behavior in a pH-responsive membrane composed of a polystyrene-b-poly(4-vinylpyridine) (PS-b-P4VP) block copolymer (BCP) when fabricated as a hierarchically-organized sandwich structure on a nanopore electrode array (NEA), i.e. BCP@NEA. At pH < pK a (P4VP) (pK a ~ 4.8), the BCP acts as an anion-exchange membrane due to the hydrophilic, protonated P4VP cylindrical nanodomains, but at pH > pK a (P4VP), the P4VP domains exhibit charge-neutral, hydrophobic and collapsed structures, blocking mass transport via the hydrophobic membrane. However, when originally prepared in a dewetted condition, mass transport in the BCP membrane may be switched on if sufficiently negative potentials are applied to the BCP@NEA architecture. When the hydrophobic BCP membrane is introduced on top of 2-electrode-embedded nanopore arrays, electrolyte solution in the nanopores is introduced, then isolated, by exploiting the potential-induced wetting and dewetting transitions in the BCP membrane. The potential-induced wetting/dewetting transition and the effect on cyclic voltammetry in the BCP@NEA structures is characterized as a function of the potential, pH and ionic strength. Additionally chronoamperometry and redox cycling experiments are used to further characterize the potential response. The multi-modal mass transport system proposed in this work will be useful for ultrasensitive sensing and single-molecule studies, which require long-time monitoring to explore reaction dynamics as well as molecular heterogeneity in nanoconfined volumes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-efficiency frost and ice control via sensing-assisted nanovibrational slippery surfaces

Frost and ice accretions on surfaces pose persistent challenges across numerous industrial, residential and transportation systems. While various removal strategies exist, they often suffer from limited effectiveness or high energy consumption, such as frosting delay, ice crack generation, and Joule heating. Here, in this work, we report a novel integrated approach combining vibrational quasi-liquid surface (QLS) and capacitive sensing for efficient condensate, frost, and ice management. Compared to Joule heating, our approach does not rely on complete melting and evaporation for removal, resulting in 68% and 95% energy savings for frost and ice removal, respectively. Our QLS coating significantly reduces surface retention forces, achieving 91% and 87% less residual mass compared to hydrophilic surfaces for frost and ice removal through surface nanovibration, respectively. The integrated capacitive sensor provides real-time detection of different phase states, enabling on-demand removal in precise timeframes. This sensor-assisted approach showed 3.8 times lower energy consumption compared to conventional Joule heating for defrosting. This synergistic integration of surface engineering, nanovibration, and intelligent sensing represents a significant advancement in phase change processes, offering an energy-efficient solution for frost and ice mitigation in energy-intensive systems.

Shen, Yuchen [Univ. of Texas at Dallas, Richardson↗