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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 361 records · Page 20

Recent Progress on Surface Water Quality Models Utilizing Machine Learning Techniques

Surface waterbodies are heavily exposed to pollutants caused by natural disasters and human activities. Empowering sensor technologies in water quality monitoring, sufficient measurements have become available to develop machine learning (ML) models. Numerous ML models have quickly been adopted to predict water quality indicators in various surface waterbodies. This paper reviews 78 recent articles from 2022 to October 2024, categorizing water quality models utilizing ML into three groups: Point-to-Point (P2P), which estimates the current target value based on other measurements at the same time point; Sequence-to-Point (S2P), which utilizes previous time series data to predict the target value at one time point ahead; and Sequence-to-Sequence (S2S), which uses previous time series data to forecast sequential target values in the future. The ML models used in each group are classified and compared according to water quality indicators, data availability, and model performance. Widely used strategies for improving performance, including feature engineering, hyperparameter tuning, and transfer learning, are recognized and described to enhance model effectiveness. The interpretability limitations of ML applications are discussed. This review provides a perspective on emerging ML for surface water quality models.

machine learning (ML)↗

Measurement of heat pump processes induced by laser radiation

A series of experiments was performed in which a suitably tuned CO2 laser, frequency doubled by a Tl3AsSe37 crystal, was brought into resonance with a P-line or two R-lines in the fundamental vibration spectrum of CO. Cooling or heating produced by absorption in CO was measured in a gas-thermometer arrangement. P-line cooling and R-line heating could be demonstrated, measured, and compared. The experiments were continued with CO mixed with N2 added in partial pressures from 9 to 200 Torr. It was found that an efficient collisional resonance energy transfer from CO to N2 existed which increased the cooling effects by one to two orders of magnitude over those in pure CO. Temperature reductions in the order of tens of degrees Kelvin were obtained by a single pulse in the core of the irradiated volume. These measurements followed predicted values rather closely, and it is expected that increase of pulse energies and durations will enhance the heat pump effects. The experiments confirm the feasibility of quasi-isentropic engines which convert laser power into work without the need for heat rejection. Of more immediate potential interest is the possibility of remotely powered heat pumps for cryogenic use, such applications are discussed to the extent possible at the present stage.

Garbuny, M.↗

Performance analysis of parallel branch and bound search with the hypercube architecture

With the availability of commercial parallel computers, researchers are examining new classes of problems which might benefit from parallel computing. This paper presents results of an investigation of the class of search intensive problems. The specific problem discussed is the Least-Cost Branch and Bound search method of deadline job scheduling. The object-oriented design methodology was used to map the problem into a parallel solution. While the initial design was good for a prototype, the best performance resulted from fine-tuning the algorithm for a specific computer. The experiments analyze the computation time, the speed up over a VAX 11/785, and the load balance of the problem when using loosely coupled multiprocessor system based on the hypercube architecture.

Mraz, Richard T.↗

Toward a More Robust Pruning Procedure for MLP Networks

Choosing a proper neural network architecture is a problem of great practical importance. Smaller models mean not only simpler designs but also lower variance for parameter estimation and network prediction. The widespread utilization of neural networks in modeling highlights an issue in human factors. The procedure of building neural models should find an appropriate level of model complexity in a more or less automatic fashion to make it less prone to human subjectivity. In this paper we present a Singular Value Decomposition based node elimination technique and enhanced implementation of the Optimal Brain Surgeon algorithm. Combining both methods creates a powerful pruning engine that can be used for tuning feedforward connectionist models. The performance of the proposed method is demonstrated by adjusting the structure of a multi-input multi-output model used to calibrate a six-component wind tunnel strain gage.

Stepniewski, Slawomir W.↗

Robust local search for spacecraft operations using adaptive noise

Randomization is a standard technique for improving the performance of local search algorithms for constraint satisfaction. However, it is well-known that local search algorithms are constraints satisfaction. However, it is well-known that local search algorithms are to the noise values selected. We investigate the use of an adaptive noise mechanism in an iterative repair-based planner/scheduler for spacecraft operations. Preliminary results indicate that adaptive noise makes the use of randomized repair moves safe and robust; that is, using adaptive noise makes it possible to consistently achieve, performance comparable with the best tuned noise setting without the need for manually tuning the noise parameter.

planning↗

Local oscillator chain for 1.55 to 1.75 THz with 100-(mu)W peak power

We report on the design and performance of a fix-tuned x2x 3x 3 frequency multiplier chain that covers 1.55-1.75 THz. The chain is nominally pumped with 100 mW at W-band. At 120 K the measured output power is larger than 4 (mu)W across the band with a peak power of 100 (mu) W at 1.665 THz. A similar chain operated at room temperature produced a peak power of 21 (mu)W. These power levels now make it possible to deploy multipixel heterodyne imaging arrays in this frequency range.

frequency multiplier↗

Attitude and position estimation on the Mars Exploration Rovers

NASA/JPL 's Mars Exploration Rovers acquire their attitude upon command and autonomously propagate their attitude and position. The rovers use accelerometers and images of the sun to acquire attitude, autonomously searching the sky for the sun with a pointable camera. To propagate the attitude and position the rovers use either accelerometer and gyro readings or gyro readings and wheel odometiy, depending on the nature of the movement ground operators are commanding. Where necessary, visual odometry is performed on images to fine tune the position updates, particularly in high slip environments. The capability also exists for visual odometry attitude updates. This paper describes the techniques used by the rovers to acquire and maintain attitude and position knowledge, the accuracy which is obtainable, and lessons learned after more than one year in operation.

attitude estimation↗

Low Profile Tunable Dipole Antenna Using BST Varactors for Biomedical Applications

In this paper a 2.4 GHz low profile (lambda/47) tunable dipole antenna is evaluated in the presence of a human core model (HCM) body phantom. The antenna uses a frequency selective surface (FSS) with interdigital barium strontium titanate (BST) varactor-tuned unit cells and its performance is compared to a similar low profile antenna that uses an FSS with semiconductor varactor diodes. The measured data of the antenna demonstrate tunability from 2.2 GHz to 2.55 GHz in free space and impedance match improvement in the presence of a HCM at different distances. This antenna has smaller size, lower cost and less weight compared to the semiconductor varactor diode counterpart.

frequency selective surfaces↗

Low Profile Tunable Dipole Antennas Using BST Varactors for Biomedical Applications

In this presentation a 2.4 GHz low profile (lambda45) tunable dipole antenna is evaluated in the presence of a human core model (HCM) body phantom. The antenna uses a frequency selective surface (FSS) with interdigital barium strontium titanate (BST) varactor-tuned unit cells and its performance is compared to a similar low profile antenna that uses an FSS with semiconductor varactor diodes. The measured data of the antenna demonstrate tunability from 2.2 GHz to 2.55 GHz in free space and impedance match improvement in the presence of a HCM at different distances. This antenna has smaller size, lower cost and less weight compared to the semiconductor varactor diode counterpart.

Tunable Dipole Antennas↗

Model-Based Control of an Aircraft Engine using an Optimal Tuner Approach

This paper covers the development of a model-based engine control (MBEC) method- ology applied to an aircraft turbofan engine. Here, a linear model extracted from the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS40k) at a cruise operating point serves as the engine and the on-board model. The on-board model is up- dated using an optimal tuner Kalman Filter (OTKF) estimation routine, which enables the on-board model to self-tune to account for engine performance variations. The focus here is on developing a methodology for MBEC with direct control of estimated parameters of interest such as thrust and stall margins. MBEC provides the ability for a tighter control bound of thrust over the entire life cycle of the engine that is not achievable using traditional control feedback, which uses engine pressure ratio or fan speed. CMAPSS40k is capable of modeling realistic engine performance, allowing for a verification of the MBEC tighter thrust control. In addition, investigations of using the MBEC to provide a surge limit for the controller limit logic are presented that could provide benefits over a simple acceleration schedule that is currently used in engine control architectures.

Connolly, Joseph W.↗

Semantic Search with Sentence-BERT for Design Information Retrieval

Managing and referencing design knowledge is a critical activity in the design process. However, reliably retrieving useful knowledge can be a frustrating experience for users of knowledge management systems due to inherent limitations of standard keyword-based searches. In this research, we consider the task of retrieving relevant lessons learned from the NASA Lessons Learned Information System (LLIS). To this end, we apply a state-of-the-art natural language processing (NLP) technique for information retrieval: semantic search with sentence-BERT, which is a modification of a Bidirectional Encoder Representations from Transformers (BERT) model that uses siamese and triplet network architectures to obtain semantically meaningful sentence embeddings. While the pretrained sBERT model shows excellent out-of-the-box performance, we further fine-tune the model on data from the LLIS so that it learns on design engineering-relevant vocabulary. We quantify the improvement in query results using both standard sBERT and fine-tuned sBERT over the LLIS’s built-in keyword search. Additionally, we demonstrate a use case for the query system by searching for lessons learned relevant to specific requirements from a NASA project as part of a broader knowledge management and retrieval system. Results indicate that applying state-of-the-art natural language processing techniques, especially when fine-tuned using engineering data, to design information retrieval tasks shows significant promise in modernizing design knowledge management systems.

Hannah S. Walsh↗

Microcanonical Hamiltonian Monte Carlo

We develop Microcanonical Hamiltonian Monte Carlo (MCHMC), a class of models that follow fixed energy Hamiltonian dynamics, in contrast to Hamiltonian Monte Carlo (HMC), which follows canonical distribution with different energy levels. MCHMC tunes the Hamiltonian function such that the marginal of the uniform distribution on the constant-energy-surface over the momentum variables gives the desired target distribution. We show that MCHMC requires occasional energy-conserving billiard-like momentum bounces for ergodicity, analogous to momentum resampling in HMC. We generalize the concept of bounces to a continuous version with partial direction preserving bounces at every step, which gives energy-conserving underdamped Langevin-like dynamics with non-Gaussian noise (MCLMC). MCHMC and MCLMC exhibit favorable scalings with condition number and dimensionality. We develop an efficient hyperparameter tuning scheme that achieves high performance and consistently outperforms NUTS HMC on several standard benchmark problems, in some cases by orders of magnitude.

97 MATHEMATICS AND COMPUTING↗

Modeling Heat Pipes with Non-Condensable Gases

The report showcases advancements in modeling heat pipes, considering both scenarios with and without non-condensable gases. To achieve this, two distinct modeling approaches are juxtaposed. Firstly, the effective conduction model, implemented in the MOOSE-based code Sockeye, is employed. Secondly, a first-of-a-kind two-phase Euler-Euler Computational Fluid Dynamics (CFD) model is developed using the STAR-CCM+ code. Both models undergo validation against experimental data, acknowledging the inherent uncertainties associated with each modeling assumption. Interestingly, the non-tuned CFD model surpasses the performance of the calibrated conduction model for heat pipes operating under both conditions: with and without non-condensable gases. It's worth noting, however, that the CFD models entail significantly longer runtimes compared to the conduction models. Nevertheless, the insights garnered from the CFD model shed invaluable light on the intricate operational dynamics of heat pipes. Future work involves broadening the validation scope of these models and continuing their development to enhance their utility as robust tools for heat pipe design and operational support.

42 ENGINEERING↗

Microwave-assisted pyrolysis of hydrocarbons using iron-based alumina catalysts obtained via solution combustion synthesis

The demand for hydrogen is growing which makes the development of clean and efficient H2 synthesis technologies imperative. Microwave-assisted, thermocatalytic, dehydrogenation of hydrocarbons has demonstrated the ability to generate H2 with high yield and selectivity, leaving behind valuable solid carbon byproducts. However, this microwave-assisted process is unoptimized which prevents it from being utilized in industry. A critical component of optimization is the development of a catalyst that is catalytically active, a good microwave absorber, and can be regenerated for repeated dehydrogenation cycles. Previous studies that focused on plastic waste decomposition have used iron-based alumina (FeAlxOy) made via solution combustion synthesis (SCS). Unexplored is the effect of tuning SCS parameters on dehydrogenation performance, the use of these materials in hydrocarbon decomposition to H2, and the regeneration of these catalysts. This dissertation has three objectives: (1) characterize the relationship between SCS parameters and the material properties of FeAlxOy, (2) determine how differences in the material properties of FeAlxOy influence their performance as catalysts during microwave-assisted pyrolysis of fossil fuels, and (3) investigate the Boudouard reaction to regenerate the FeAlxOy post-dehydrogenation.

Chanoi, Zachary Aidan↗

Tailored mesoporous structures of lignin-derived nano-carbons for multiple applications

This work uses a one-step KOH activation for lignin precursors to produce ultra-high mesoporous activated carbons (ACs) with an unprecedented combination of the surface area of 3207 m 2 g -1 and mesopore ratio of 76%. The ACs are applied for supercapacitors (SCs) and methylene blue (MB) adsorption. The capacitance of the SCs in the three-electrode system reaches 812.3 F g -1 and demonstrates a remarkable maximum MB adsorption capacity of 1250 mg g -1 . By modifying the process conditions, the mesopore ratio of ACs could be controlled from 10% to 80%. Compared with one-step activation, a two-step method produced microporous carbons with a lower surface area of 1227 m 2 g -1 and a high micropore ratio of 73%. The capacitance of SCs with two-step ACs reached 228.1 F g -1 and the maximum adsorption capacity of 476.19 mg g -1 for MB adsorption. The two-step method limited the surface area but had a higher oxygen surface functionality, benefiting its electrochemical performance. A techno-economic analysis reveals that the one-step KOH activation-based process develops ACs with a minimum selling price of $7648/ton. In conclusion, this work demonstrates tuning the processing-structure-property-performance relationship of lignin-based ACs to make an economically viable domestic carbon source.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

MatRIS: Multi-level Math Library Abstraction for Heterogeneity and Performance Portability using IRIS Runtime

Vendor libraries are tuned for a specific architecture and are not portable to others. Moreover, they lack support for heterogeneity and multi-device orchestration, which is required for efficient use of contemporary HPC and cloud resources. To address these challenges, we introduce MatRIS—a multilevel math library abstraction for scalable and performance-portable sparse/dense BLAS/LAPACK operations using IRIS runtime. The MatRIS-IRIS co-design introduces three levels of abstraction to make the implementation completely architecture agnostic and provide highly productive programming. We demonstrate that MatRIS is portable without any change in source code and can fully utilize multi-device heterogeneous systems by achieving high performance and scalability on Summit, Frontier, and a CADES cloud node equipped with four NVIDIA A100 GPUs and four AMD MI100 GPUs. A detailed performance study is presented in which MatRIS demonstrates multi-device scalability. When compared, MatRIS provides competitive and even better performance than libraries from vendors and other third parties.

Monil, M. A. H.↗

Bringing HPE Slingshot 11 support to Open MPI

The Cray HPE Slingshot 11 network is used on the new exascale systems arriving at the U.S. Department of Energy (DoE) laboratories (e.g., Frontier, Aurora, Perlmutter). As such, the support of this network is an important capability to meet the needs of exascale applications. Here, this article highlights recent work to develop supporting infrastructure to enable Open MPI to efficiently support these new platforms. A key component of this effort involves development of a new Open Fabrics Interface (OFI) provider, LinkX. We discuss the design and development of enhancements that take advantage of the new Slingshot 11 network and AMD GPUs. We include performance data from tests on the Frontier supercomputer using synthetic communication benchmarks, and the vendor provided MPI as a baseline for comparison. The tests demonstrate full functionality of Open MPI on the system and initial results show favorable performance when compared to the highly tuned vendor implementation.

97 MATHEMATICS AND COMPUTING↗