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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 991 records · Page 55

A Discrete and Distributed Steady Blowing Application on a High Reynolds Number Semispan Supercritical Wing Configuration

The FAST-MAC circulation control model was modified to test an array of steady and unsteady actuators at realistic flight Reynolds numbers in the National Transonic Facility at the NASA Langley Research Center. Previous experiments in the FAST-MAC test series used a fullspan tapered slot, and that configuration is used as a baseline for performance and weight flow requirements. The goal of the latest experiment was to reduce the weight flow required to achieve comparable performance established by the baseline FAST-MAC data. Thirty-nine interchangeable actuator cartridges of various designs were mounted into the FAST-MAC model where the exiting jet was directed over a 15% chord simple hinged-flap. These two types of actuators were fabricated using rapid prototype techniques and their design performance was optimized for a transonic cruise configuration having a 0° flap deflection. The steady actuators were found to provide an off-design drag reduction of 5.5%, nearly equaling the drag reduction of the fullspan tapered slot configuration, but with a 69% weight flow reduction. This weight flow savings is similar to the sweeping jet actuators, but with better drag performance.

Jones, Gregory S.↗

HydraGNN v5.0

HydraGNN v5.0 expands the code base into a more portable, scalable, and flexible framework for scientific graph learning, with particular strength in atomistic machine-learning interatomic potentials and large-scale distributed training. The release adds Fully Sharded Data Parallel (FSDP) support alongside existing DDP and DeepSpeed paths, including FSDP-aware checkpointing and optimizer integration, and introduces a configurable multi-precision training workflow supporting FP32, BF16, and FP64 across GPUs and Intel XPUs. For atomistic modeling, HydraGNN v5.0 strengthens its MLIP capabilities through dynamic graph construction at every forward pass, energy-conserving force prediction via automatic differentiation, and per-atom energy loss formulations, while extending EGNN models to properly handle periodic boundary conditions. The release also broadens model expressiveness through graph-level attribute conditioning, adds new multi-task and model-parallel extensions such as MACE support and encoder/decoder branch optimization, and expands application coverage with integrated examples for datasets including OC25, Nabla2-DFT, QCML, Open Polymers 2026, and OPF. In parallel, HydraGNN v5.0 improves production readiness through performance optimizations for large-scale runs, stratified sampling and linear-regression preprocessing utilities, and tested installation scripts for DOE supercomputers including Frontier, Aurora, Perlmutter, and Andes. Overall, the release advances HydraGNN as a robust software platform for scalable graph neural networks across materials science, chemistry, and scientific machine learning workflows

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗

Methodology and method and apparatus for signaling with capacity optimized constellations

Communication systems having transmitter, includes a coder configured to receive user bits and output encoded bits at an expanded output encoded bit rate, a mapper configured to map encoded bits to symbols in a symbol constellation, a modulator configured to generate a signal for transmission via the communication channel using symbols generated by the mapper. In addition, the receiver includes a demodulator configured to demodulate the received signal via the communication channel, a demapper configured to estimate likelihoods from the demodulated signal, a decoder that is configured to estimate decoded bits from the likelihoods generated by the demapper. Furthermore, the symbol constellation is a capacity optimized geometrically spaced symbol constellation that provides a given capacity at a reduced signal-to-noise ratio compared to a signal constellation that maximizes d.sub.min.

Barsoum, Maged F.↗

Optimizing the query performance of block index through data analysis and I/O modeling

Indexing technique has become an efficient tool to enable scientists to directly access the most relevant data records. But, the time and space requirements of building and storing indexes are expensive in the traditional approaches, such as R-tree and bitmaps. Recently, we started to address this issue by using the idea of "block index", and our previous work has shown promising results from comparing it against other well-known solutions, including ADIOS, SciDB, and FastBit. In this work, we further improve the technique from both theoretical and implementation perspectives. Driven by an extensive effort in characterizing scientific datasets and modeling I/O systems, we presented a theoretical model to analyze its query performance with respect to a given block size configuration. We also introduced three optimization techniques to achieve a 2.3x query time reduction comparing to the original implementation.

Wu, Tzuhsien↗

The use of multi-objective optimization to improve the design process of nuclear power plant systems

Multi-objective optimization is proposed to address the problem of design optimality in the nuclear power plant design process. This is done via the creation/development of the Optimization and Preference Tool for the Improvement of Nuclear Systems (OPTIONS). This work details applications of multi-objective optimization methods (in Python 3) to two different nuclear system design problems: the flash-Rankine power conversion system (PCS) of the I 2 S-LWR and the Passive Endothermic Reaction Cooling System (PERCS) attached to a standard PWR primary system (in RELAP5). The PCS design problem is first solved for three configurations using a specific particle swarm optimization method, achieving a thermodynamic efficiency of 34.81%. A new method, the Mixed-Integer Non-dominated Sorting Genetic Algorithm (MI-NSGA), is created and then used, solving a PCS superstructure of 22 configurations and achieving an efficiency of 35.63%. Finally, the OPTIONS tool is used to optimize the PERCS, improving cost, core temperature control, and cooling longevity.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Evolving Requirements for Magnetic Tape Data Storage Systems

Magnetic tape data storage systems have evolved in an environment where the major applications have been back-up/restore, disaster recovery, and long term archive. Coincident with the rapidly improving price-performance of disk storage systems, the prime requirements for tape storage systems have remained: (1) low cost per MB, (2) a data rate balanced to the remaining system components. Little emphasis was given to configuring the technology components to optimize retrieval of the stored data. Emerging new applications such as network attached high speed memory (HSM), and digital libraries, place additional emphasis and requirements on the retrieval of the stored data. It is therefore desirable to consider the system to be defined both by STorage And Retrieval System (STARS) requirements. It is possible to provide comparative performance analysis of different STARS by incorporating parameters related to (1) device characteristics, and (2) application characteristics in combination with queuing theory analysis. Results of these analyses are presented here in the form of response time as a function of system configuration for two different types of devices and for a variety of applications.

Gniewek, John J.↗

Techno-Economic Analysis and Global Warming Potential of a Novel Offshore Macroalgae Biorefinery

The success of a large scale macroalgae-based biorefinery is dependent on the demonstration of favorable system economics and environmental sustainability. This study uses detailed process modeling to quantify the mass and energy flows through the various unit operations required for a novel free-floating macroalgae biorefinery concept. The modular process model served as the foundation for the techno-economic and global warming potential analyses used to quantify the sustainability of the proposed concept. This work includes detailed techno-economic results for a complete macroalgae cultivation and conversion system with multiple hatchery configurations and several emerging technologies. System optimization was achieved through the evaluation of various technology options for each unit operation. Technologies considered include traditional twine and textile substrate hatchery configurations, drone assisted seeding and biomass transport, mechanized line seeding and harvesting, adhesive spore mixtures that simplify seeding operations and improve hatchery energetics, and hydrothermal liquefaction to produce upgradable biocrude. Outputs from the system include renewable diesel (R100), naphtha, biochar, nitrogen and phosphorus fertilizers, and aqueous/solid waste streams. Three different system pathways were explored, yielding a biomass production cost ranging from $210 to $565 per dry metric ton and a minimum fuel selling price from $1.35 to $2.91 per liter of gasoline equivalent. Stochastic manipulation of the process model and sensitivity analyses support these results. The global warming potential analysis shows net greenhouse gas emissions ranging from 14 to 29 gCO2-eq MJ-1, supported by stochastic and sensitivity analyses. The recommendations from this work highlight critical areas for research and development investment such that a sustainable macroalgae cultivation and conversion system can be realized.

NOMAD seaweed cultivation, techno-economic analysi↗

Optimal environmental and economic performance trade-offs for fifth generation district heating and cooling network topologies with waste heat recovery

Network topology greatly influences both the economic and environmental performance of fifth generation district heating and cooling (5GDHC) systems. In this study the optimal trade-offs between the environmental and economic performance of 5GDHC network topologies for a five-building district with waste heat recovery were explored. A life cycle assessment method was used to calculate the total life cycle CO 2 emissions (LCCO2) associated with the installation and operation of various network topologies. Twelve months of empirical data from a data center cooling system were analyzed to assess its suitability for integration into a 5GDHC system. The most suitable method for utilizing this waste heat was selected based on the ambient loop warm pipe setpoint, waste heat temperature, and district energy system configuration. A multi-objective optimization algorithm was used to select the 5GDHC network topology that provided the optimal trade-off between LCCO2 and life cycle cost (LCC). A trade-off parameter was employed to weigh the importance of each objective in the selection process. The results showed waste heat from the data center was suitable for integration into the 5GDHC system due to its availability and consistent temperature profile. When return temperatures of 25 °C or higher were available from the liquid-cooled system, direct pre-heating of the ambient loop warm pipe was found to be the most effective waste heat integration method. The selection of the network topology that provided the optimal trade-off between LCCO2 and LCC (optimal trade-off topology) was highly dependent on factors such as fuel prices, CO 2 prices, electricity CO 2 emissions factors, availability of waste heat, embodied CO 2 emissions associated with network installation and network infrastructure costs. Optimal trade-off topologies produced substantial LCCO2 reductions relative to corresponding LCC increases. LCCO2 reduction to LCC increase ratios from 5.78 to 117.79 were identified with CO 2 offset costs ranging from 4.77 to 60.08 ($/tCO 2 e).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Linear Transformation of Electromagnetic Wave Beams of the Electron-Cyclotron Range in Toroidal Magnetic Configurations

The field structure of quasi-optical wave beams tunneled through the evanescence region in the vicinity of the plasma cutoff in a nonuniform magnetoactive plasma is analyzed. This problem is traditionally associated with the process of linear transformation of ordinary and extraordinary waves. An approximate analytical solution is constructed for a rather general magnetic configuration applicable to spherical tokamaks, optimized stellarators, and other magnetic confinement systems with a constant plasma density on magnetic surfaces. A general technique for calculating the transformation coefficient of a finite-aperture wave beam is proposed, and the physical conditions required for the most efficient transformation are analyzed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Machine Learning-Based Temperature Prediction for Runtime Thermal Management Across System Components

Elevated temperatures limit the peak performance of systems because of frequent interventions by thermal throttling. Non-uniform thermal states across system nodes also cause performance variation within seemingly equivalent nodes leading to significant degradation of overall performance. In this paper we present a framework for creating a lightweight thermal prediction system suitable for run-time management decisions. We pursue two avenues to explore optimized lightweight thermal predictors. First, we use feature selection algorithms to improve the performance of previously designed machine learning methods. Second, we develop alternative methods using neural network and linear regression-based methods to perform a comprehensive comparative study of prediction methods. We show that our optimized models achieve improved performance with better prediction accuracy and lower overhead as compared with the Gaussian process model proposed previously. Specifically we present a reduced version of the Gaussian process model, a neural network-based model, and a linear regression-based model. Using the optimization methods, we are able to reduce the average prediction errors in the Gaussian process from 4: 2 degrees C to 2: 9 degrees C. We also show that the newly developed models using neural network and Lasso linear regression have average prediction errors of 2: 9 degrees C and 3: 8 degrees C respectively. The prediction overheads are 0.22, 0.097, and 0.026 ms per prediction for reduced Gaussian process, neural network, and Lasso linear regression models, respectively, compared with 0.57 ms per prediction for the previous Gaussian process model. We have implemented our proposed thermal prediction models on a two-node system configuration to help identify the optimal task placement. The task placement identified by the models reduces the average system temperature by up to 11: 9 degrees C without any performance degradation. Furthermore, these models respectively achieve 75, 82.5, and 74.17 percent success rates in correctly pointing to those task placements with better thermal response, compared with 72.5 percent success for the original model in achieving the same objective. Lastly, we extended our analysis to a 16-node system and we were able to train models and execute them in real time to guide task migration and achieve on average 17 percent reduction in the overall system cooling power.

97 MATHEMATICS AND COMPUTING↗

Elaborated Odor Test for Extended Exposure

Concerns were raised when incidental exposure to a proprietary bonding material revealed the material had an irritating odor. The NASA-STD-6001B document describes a supplemental test method option for programs to evaluate materials with odor concerns (Test 6, Odor Assessment). In addition to the supplemental standard odor assessment with less than 10 seconds of exposure, the NASA White Sands Test Facility (WSTF) Materials Flight Acceptance Testing section was requested to perform an odor test with an extended duration to evaluate effects of an extended exposure and to more closely simulate realistic exposure scenarios. With approval from the NASA Johnson Space Center Industrial Hygienist, WSTF developed a 15-minute odor test method. WSTF performed this extended-duration odor test to evaluate the odor and physical effects of the bonding material configured between two aluminum plates, after the safety of the gas was verified via toxicity analysis per NASA-STD-6001B Test 7, Determination of Offgassed Products. During extended-duration testing, odor panel members were arranged near the test material in a small room with the air handlers and doors closed to minimize dilution. The odor panel members wafted gas toward themselves and recorded their individual assessments of odor and physical effects at various intervals during the 15-minute exposure and posttest. A posttest interview was conducted to obtain further information. Testing was effective in providing data for comparison and selection of an optimal offgassing and odor containment configuration. The developed test method for extended exposure is proposed as a useful tool for further evaluating materials with identified odors of concern if continued use of the material is anticipated.

Buchanan, Vanessa D.↗

Enabling Production of Algal Biofuels by Techno-Economic Optimization of Co-Product Suites

Recent techno-economic analysis (TEA) has underscored that for algal biofuels to be cost competitive with petroleum fuels, co-products are necessary to offset the cost of fuel production. The co-product suite must scale with fuel production while also maximizing value from the non-fuel precursor components. The co-product suite also depends on algal biomass composition, which is highly dynamic and depends on environmental conditions during cultivation. Intentional shifts in composition during cultivation are often associated with reduced biomass productivity, which can increase feedstock production costs for the algae-based biorefinery. The optimal algae-based biorefinery configuration is thus a function of many factors. We have found that comprehensive TEA, which requires the construction of process models with detailed mass and energy balances, along with a complete accounting of capital and operating expenditures for a commercial-scale production facility, provides invaluable insight into the viability of a proposed biorefinery configuration. This insight is reflected in improved viability for one biorefining approach that we have developed over the last 10 years, namely, the Combined Algal Processing (CAP) approach. This approach fractionates algal biomass into carbohydrate-, lipid-, and protein-rich fractions, and tailors upgrading chemistry to the composition of each fraction. In particular, transitioning from valorization of only the lipids to a co-product suite from multiple components of high-carbohydrate algal biomass can reduce the minimum fuel selling price (MFSP) from more than $8/gallon of gasoline equivalent (GGE) to $2.50/GGE. This paper summarizes that progress and discusses several surprising implications in this optimization approach.

09 BIOMASS FUELS↗

Influence of optimized leading-edge deflection and geometric anhedral on the low-speed aerodynamic characteristics of a low-aspect-ratio highly swept arrow-wing configuration

An investigation conducted in the Langley 7 by 10 foot tunnel to determine the influence of an optimized leading-edge deflection on the low speed aerodynamic performance of a configuration with a low aspect ratio, highly swept wing. The sensitivity of the lateral stability derivative to geometric anhedral was also studied. The optimized leading edge deflection was developed by aligning the leading edge with the incoming flow along the entire span. Owing to spanwise variation of unwash, the resulting optimized leading edge was a smooth, continuously warped surface for which the deflection varied from 16 deg at the side of body to 50 deg at the wing tip. For the particular configuration studied, levels of leading-edge suction on the order of 90 percent were achieved. The results of tests conducted to determine the sensitivity of the lateral stability derivative to geometric anhedral indicate values which are in reasonable agreement with estimates provided by simple vortex-lattice theories.

Coe, P. L., Jr.↗

Exploratory investigation of aeroacoustic optimization of the variable impedance edge concept applied to upper surface blown configurations

The feasibility of using porous surfaces on lift augmentation flaps to reduce the noise at the source, without adversely affecting aerodynamic performance was investigated. Numerous flap configurations were tested on a USB (upper surface blowing) type powered lift model (approximately 1/5 full scale). Significant reductions of far field noise and aeroacoustic pressures were found, and many configurations exhibited aerodynamic characteristics comparable to unmodified configurations of the nozzle/flap system.

Hayden, R. E.↗

Aerodynamic control of NASP-type vehicles through Vortex manipulation. Volume 2: Static wind tunnel tests

Forebody Vortex Control (FVC) was explored in this research program for potential application to a NASP-type configuration. Wind tunnel tests were conducted to evaluate a number of jet blowing schemes. The configuration tested has a slender forebody and a 78 deg swept delta wing. Blowing jets were implemented on the leeward side of the forebody with small circular tubes tangential to the surface that could be directed aft, forward, or at angles in between. The effects of blowing are observed primarily in the yawing and rolling moments and are highly dependent on the jet configuration and the angle of attack. Results show that the baseline flow field, without blowing activated, is quite sensitive to the geometry differences of the various protruding jets, as well as being sensitive to the blowing, particularly in the angle of attack range where the forebody vortices are naturally asymmetric. The time lag of the flow field response to the initiation of blowing was also measured. The time response was very short, on the order of the time required for the flow disturbance to travel the distance from the nozzle to the specific airframe location of interest at the free stream velocity. Overall, results indicate that sizable yawing and rolling moments can be induced with modest blowing levels. However, direct application of this technique on a very slender forebody would require thorough wind tunnel testing to optimize the jet location and configuration.

Suarez, Carlos J.↗

Space Shuttle 2 advanced space transportation system, volume 2

To determine the best configuration from all candidate configurations, it was necessary first to calculate minimum system weights and performance. To optimize the design, it is necessary to vary configuration-specific variables such as total system weight, thrust-to-weight ratios, burn durations, total thrust available, and mass fraction for the system. Optimizing each of these variables at the same time is technically unfeasible and not necessarily mathematically possible. However, discrete sets of data can be generated which will eliminate many candidate configurations. From the most promising remaining designs, a final configuration can be selected. Included are the three most important designs considered: one which closely approximates the design criteria set forth in a Marshall Space Flight Center study of the Shuttle 2; the configuration used in the initial proposal; and the final configuration. A listing by cell of the formulas used to generate the aforementioned data is included for reference.

Adinaro, James N.↗

Optimal lifting ascent trajectories for the space shuttle

The performance gains which are possible through the use of optimal trajectories for a particular space shuttle configuration are discussed. The spacecraft configurations and aerodynamic characteristics are described. Shuttle mission payload capability is examined with respect to the optimal orbit inclination for unconstrained, constrained, and nonlifting conditions. The effects of velocity loss and heating rate on the optimal ascent trajectory are investigated.

Rau, T. R.↗

Optimization-Based Azeotropic Distillation System Synthesis Using Geometric Insights

The synthesis of azeotropic distillation systems is challenging due to the existence of compartments in the residue curve map coupled with the combinatorial aspects from numerous possible system configurations. In this work, an optimization-based approach is introduced to synthesize homogeneous azeotropic distillation systems. The approach employs a network-based representation generated via a matrix method. To design the distillation columns, the modified Underwood equations are adopted, in which pseudocomponent-based compositions are used. For cases where separatrices are significantly curved, corrections via piece-wise linear functions and collinearity properties are implemented. Two examples are presented to illustrate the proposed approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗