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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Avoiding compressor surge during emergency shutdown hybridturbine systems

A new emergency shutdown procedure for a direct-fired fuel cell turbine hybrid power system was evaluated using a hardware-based simulation of an integrated gasifier/fuel cell/turbine hybrid cycle (IGFC), implemented through the Hybrid Performance (Hyper) project at the National Energy Technology Laboratory, U.S. Department of Energy (NETL). The Hyper facility is designed to explore dynamic operation of hybrid systems and quantitatively characterize such transient behavior. It is possible to model, test, and evaluate the effects of different parameters on the design and operation of a gasifier/fuel cell/gas turbine hybrid system and provide a means of quantifying risk mitigation strategies. An open-loop system analysis regarding the dynamic effect of bleed air, cold air bypass, and load bank is presented in order to evaluate the combination of these three main actuators during emergency shutdown. In the previous Hybrid control system architecture, catastrophic compressor failures were observed when the fuel and load bank were cut off during emergency shutdown strategy. Improvements were achieved using a nonlinear fuel valve ramp down when the load bank was not operating. Experiments in load bank operation show compressor surge and stall after emergency shutdown activation. The difficulties in finding an optimal compressor and cathode mass flow for mitigation of surge and stall using these actuators are illustrated.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Chatbots can guide experimentalists to avoid many common mistakes in measuring fluorescence spectra

The concepts of fluorescence spectroscopy are well established, yet the experimental collection of a spectrum is susceptible to a range of errors. A recent study showed that chatbots – derived from substantial advances in artificial intelligence – can provide practical assistance to the experimentalist during collection of absorption spectra and thereby achieve improved quality. Fluorescence, while the complement of absorption, is prone to a far richer array of experimental errors encompassing environmental factors, instrumental settings, and experimentalist mistakes. Here, 10 chatbots (ChatGPT 5, Gemini 2.5 Pro, Microsoft Copilot, Meta AI Llama 4, Claude Sonnet 4.5, X.ai Grok 4, Perplexity Pro, DeepSeek V3.1, Z.ai GLM-4.6, and KIMI K2) have been evaluated for the suitability in providing quality-improvement advice to the experimentalist during acquisition of fluorescence spectra. Significant opportunities for practical assistance are noted, although intervention by a domain expert is often required. Here, if combined with image recognition and/or signal processing, chatbots embedded in instruments may enable real-time guidance during fluorescence data acquisition.

Artificial intelligence↗
DOE OSTI2016

SU-F-T-388: Comparison of Biophysical Indices in Hippocampal-Avoidance Whole Brain VMAT and IMRT Radiation Therapy Treatment Plans

Purpose: To compare biophysical indices of Volumetric Modulated Arc Therapy (VMAT) and Intensity Modulated Radiation Therapy (IMRT) treatment plans for whole brain radiation therapy following the NRG-CC001 protocol. Methods: In this retrospective study, a total of fifteen patients were planned with Varian Eclipse Treatment Planning System using VMAT (RapidArc) and IMRT techniques. The planning target volume (PTV) was defined as the whole brain volume excluding a uniform three-dimensional 5mm expansion of the hippocampus volume. Prescribed doses in all plans were 30 Gy delivered over 10 fractions normalized to a minimum of 95% of the target volume receiving 100% of the prescribed dose. The NRG Oncology protocol guidelines were followed for contouring and dose-volume constraints. A single radiation oncologist evaluated all treatment plans. Calculations of statistical significance were performed using Student’s paired t-test. Results: All VMAT and IMRT plans met the NRG-CC001 protocol dose-volume criteria. The average equivalent uniform dose (EUD) for the PTV for VMAT vs. IMRT was respectively (19.05±0.33 Gy vs. 19.38±0.47 Gy) for α/β of 2 Gy and (19.47±0.30 Gy vs. 19.84±0.42 Gy) for α/β of 10 Gy. For the PTV, the average mean and maximum doses were 2% and 5% lower in VMAT plans than in IMRT plans, respectively. The average EUD and the normal tissue complication probability (NTCP) for the hippocampus in VMAT vs. IMRT plans were (15.28±1.35 Gy vs. 15.65±0.99 Gy, p=0.18) and (0.305±0.012 Gy vs. 0.308±0.008 Gy, p=0.192), respectively. The average EUD and NTCP for the optic chiasm were both 2% higher in VMAT than in IMRT plans. Conclusion: Though statistically insignificant, VMAT plans indicate a lower hippocampus EUD than IMRT plans. Also, a small variation in NTCP was found between plans.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Building two-dimensional materials one row at a time: Avoiding the nucleation barrier

Assembly of two-dimensional (2D) molecular arrays on surfaces produces a wide range of architectural motifs exhibiting unique properties, but little attention has been given to the mechanism by which they nucleate. Using peptides selected for their binding affinity to molybdenum disulfide, we investigated nucleation of 2D arrays by molecularly resolved in situ atomic force microscopy and compared our results to molecular dynamics simulations. The arrays assembled one row at a time, and the nuclei were ordered from the earliest stages and formed without a free energy barrier or a critical size. The results verify long-standing but unproven predictions of classical nucleation theory in one dimension while revealing key interactions underlying 2D assembly.

Chen, Jiajun (ORCID:0000000240616219)↗
DOE OSTI2026

Data sharing helps avoid “smoking gun” claims of topological milestones

Manipulating the topology of electronic bands can realize new states of matter, with possible implications for information technology. A central question is how to tell whether a topological regime has been achieved. Experiments are often guided by a prediction of a distinct and self-explanatory signal called “the smoking gun.” However, in micrometer- or nanometer-scale specimens, phenomenology can mimic the anticipated behavior without containing the exotic states. We show limited data that are consistent with the presence of four topological phenomena; by considering additional data, we identified the most likely origins of the observed patterns as trivial. Finally, we argue that the reliability of smoking gun–type claims can be greatly enhanced by releasing comprehensive datasets, discussing alternative scenarios, and disclosing the total volume of study.

Frolov, S. M. [Univ. of Pittsburgh, PA (United Sta↗
DOE OSTI2018

Importance of Neutralizing Monoclonal Antibodies Targeting Multiple Antigenic Sites on the Middle East Respiratory Syndrome Coronavirus Spike Glycoprotein To Avoid Neutralization Escape

Middle East respiratory syndrome coronavirus (MERS-CoV) causes a highly lethal pulmonary infection with ~35% mortality. The potential for a future pandemic originating from animal reservoirs or health care-associated events is a major public health concern. There are no vaccines or therapeutic agents currently available for MERS-CoV. Using a probe-based single B cell cloning strategy, we have identified and characterized multiple neutralizing monoclonal antibodies (MAbs) specifically binding to the receptor-binding domain (RBD) or S1 (non-RBD) regions from a convalescent MERS-CoV-infected patient and from immunized rhesus macaques. RBD-specific MAbs tended to have greater neutralizing potency than non-RBD S1-specific MAbs. We report six RBD-specific and five S1-specific MAbs could be sorted into four RBD and three non-RBD distinct binding patterns, based on competition assays, mapping neutralization escape variants, and structural analysis. We determined cocrystal structures for two MAbs targeting the RBD from different angles and show they can bind the RBD only in the “out” position. We then showed that selected RBD-specific, non-RBD S1-specific, and S2-specific MAbs given prophylactically prevented MERS-CoV replication in lungs and protected mice from lethal challenge. Importantly, combining RBD- and non-RBD MAbs delayed the emergence of escape mutations in a cell-based virus escape assay. These studies identify MAbs targeting different antigenic sites on S that will be useful for defining mechanisms of MERS-CoV neutralization and for developing more effective interventions to prevent or treat MERS-CoV infections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Plateau Phenomenon in Gradient Descent Training of RELU Networks: Explanation, Quantification, and Avoidance

The ability of neural networks to provide ‘best in class’ approximation across a wide range of applications is well-documented. Nevertheless, the powerful expressivity of neural networks comes to naught if one is unable to effectively train (choose) the parameters defining the network. In general, neural networks are trained by gradient descent type optimization methods,a stochastic variant thereof. In practice, such methods result in the loss function decreases rapidly at the beginning of training but then, after a relatively small number of steps, significantly slow down. The loss may even appear to stagnate over the period of a large number of epochs, only to then suddenly start to decrease fast again for no apparent reason. This so-called plateau phenomenon manifests itself in many learning tasks. The present work aims to identify and quantify the root causes of plateau phenomenon.analysis is carried out in the setting of univariate ReLU networks. No assumptions are made on the number of neurons relative to the number of training data, and our results hold for both the lazy and adaptive regimes. Here, the main findings are: plateaux correspond to periods during which activation patterns remain constant, where activation pattern refers to the number of data points that activate a given neuron; quantification of convergence of the gradient flow dynamics; and, characterization stationary points in terms solutions of local least squares regression lines over subsets of the training data. Based on these conclusions, we propose a new iterative training method, the Active Neuron Least Squares (ANLS), characterised by the explicit adjustment of the activation pattern at each step, which is designed to enable a quick exit from a plateau. Illustrative numerical examples are included throughout.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Effective Padding of Multi-Dimensional Arrays to Avoid Cache Conflict Misses

Caches are used to significantly improve performance. Even with high degrees of set-associativity, the number of accessed data elements mapping to the same set in a cache can easily exceed the degree of associativity, causing conflict misses and lowered performance, even if the working set is much smaller than cache capacity. Array padding (increasing the size of array dimensions) is a well known optimization technique that can reduce conflict misses. In this paper, we develop the first algorithms for optimal padding of arrays for a set associative cache for arbitrary tile sizes, In addition, we develop the first solution to padding for nested tiles and multi-level caches. The techniques are in implemented in PAdvisor tool. Experimental results with multiple benchmarks demonstrate significant performance improvement from use of PAdvisor for padding.

array padding↗
DOE OSTI2016

Compiler-Directed Soft Error Detection and Recovery to Avoid DUE and SDC via Tail-DMR

This article presents Clover, a compiler-directed soft error detection and recovery scheme for lightweight soft error resilience. The compiler carefully generates soft-error-tolerant code based on idempotent processing without explicit checkpoints. During program execution, Clover relies on a small number of acoustic wave detectors deployed in the processor to identify soft errors by sensing the wave made by a particle strike. To cope with DUEs (detected unrecoverable errors) caused by the sensing latency of error detection, Clover leverages a novel selective instruction duplication technique called tail-DMR (dual modular redundancy) that provides a region-level error containment. Once a soft error is detected by either the sensors or the tail-DMR, Clover takes care of the error as in the case of exception handling. To recover from the error, Clover simply redirects program control to the beginning of the code region where the error is detected. The experimental results demonstrate that the average runtime overhead is only 26%, which is a 75% reduction compared to that of the state-of-the-art soft error resilience technique. In addition, this article evaluates an alternative technique called tail-wait, comparing it to Clover. According to the evaluation with the different processor configurations and the various error detection latencies, Clover turns out to be a superior technique, achieving 1.06 to 3.49× speedup over the tail-wait.

Computer Science↗
DOE OSTI2019

A communication-avoiding 3D sparse triangular solver

We present a novel distributed memory algorithm to improve the strong scalability of the solution of a sparse triangular system. This operation appears in the solve phase of direct methods for solving general sparse linear systems, Ax = b. Our 3D sparse triangular solver employs several techniques, including a 3D MPI process grid, elimination tree parallelism, and data replication, all of which reduce the per-process communication when combined. We present analytical models to understand the communication cost of our algorithm and show that our 3D sparse triangular solver can reduce the per-process communication volume asymptotically by a factor of O(n1/4) and O(n1/6) for problems arising from the finite element discretizations of 2D "planar" and 3D "non-planar" PDEs, respectively. We implement our algorithm for use in SuperLU_DIST3D, using a hybrid MPI+OpenMP programming model. Our 3D triangular solve algorithm, when run on 12k cores of Cray XC30, outperforms the current state-of-the-art 2D algorithm by 7.2x for planar and 2.7x for the non-planar sparse matrices, respectively.

Sao, Piyush↗
DOE OSTI2021

Nomenclatural issues concerning cultured yeasts and other fungi: why it is important to avoid unneeded name changes

The unambiguous application of fungal names is important to communicate scientific findings. Names are critical for (clinical) diagnostics, legal compliance, and regulatory controls, such as biosafety, food security, quarantine regulations, and industrial applications. Consequently, the stability of the taxonomic system and the traceability of nomenclatural changes is crucial for a broad range of users and taxonomists. The unambiguous application of names is assured by the preservation of nomenclatural history and the physical organisms representing a name. Fungi are extremely diverse in terms of ecology, lifestyle, and methods of study. Predominantly unicellular fungi known as yeasts are usually investigated as living cultures. Methods to characterize yeasts include physiological (growth) tests and experiments to induce a sexual morph; both methods require viable cultures. Thus, the preservation and availability of viable reference cultures are important, and cultures representing reference material are cited in species descriptions. Historical surveys revealed drawbacks and inconsistencies between past practices and modern requirements as stated in the International Code of Nomenclature for Algae, Fungi, and Plants (ICNafp). Improper typification of yeasts is a common problem, resulting in a large number invalid yeast species names. With this opinion letter, we address the problem that culturable microorganisms, notably some fungi and algae, require specific provisions under the ICNafp. We use yeasts as a prominent example of fungi known from cultures. But viable type material is important not only for yeasts, but also for other cultivable Fungi that are characterized by particular morphological structures (a specific type of spores), growth properties, and secondary metabolites. We summarize potential proposals which, in our opinion, will improve the stability of fungal names, in particular by protecting those names for which the reference material can be traced back to the original isolate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Habitat use by female desert tortoises suggests tradeoffs between resource use and risk avoidance

Animals may select habitat to maximize the benefits of foraging on growth and reproduction, while balancing competing factors like the risk of predation or mortality from other sources. Variation in the distribution of food resources may lead animals to forage at times or in places that carry greater predation risk, with individuals in poor quality habitats expected to take greater risks while foraging. We studied Mojave desert tortoises ( Gopherus agassizii ) in habitats with variable forage availability to determine if risk aversion in their selection of habitat relative was related to abundance of forage. As a measure of risk, we examined tortoise surface activity and mortality. We also compared tortoise body size and body condition between habitats with ample forage plants and those with less forage plants. Tortoises from low forage habitats selected areas where more annual plants were nutritious herbaceous flowering plants but did not favor areas of greater perennial shrub cover that could shelter them or their burrows. In contrast, tortoises occupying high forage habitats showed no preference for forage characteristics, but used burrows associated with more abundant and larger perennial shrubs. Tortoises in high forage habitats were larger and active above ground more often but did not have better body condition. Mortality was four times higher for females occupying low forage habitat than those in high forage habitat. Our results are consistent with the idea that tortoises may minimize mortality risk where food resources are high, but may accept some tradeoff of greater mortality risk in order to forage optimally when food resources are limiting.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Assessing the Effectiveness of Generalized Likelihood Ratio Test Detector Schemes in Seismic Event Detection and the Avoidance of Nontarget Signals

Cross-correlation techniques have played a long-standing and pivotal role in seismic event monitoring. However, the performance of correlation-based detectors is challenged by nuisance seismicity, or nontarget signals. Such detections are a problem when the mission is to automatically map events to the correct source region. Using aftershocks of the 2014 $M_w$ 6.0 South Napa, California, earthquake, we demonstrate the effectiveness of utilizing a dynamic correlation processor framework in a generalized likelihood ratio test (GLRT) detector configuration to minimize nontarget detections. A GLRT maximizes a detection statistic with respect to one or more unknown parameters. In this case, the detection statistic is a template signal match against the waveform in a window sliding over a data stream, and the unknown parameter is an index variable indicating group membership of the template event or events. Detected events are assigned to the event group that yields the largest detection statistic. In this work, our results show that a GLRT detector will outperform a suite of independently operating correlation and subspace detectors in terms of having a lower nontarget detection rate at a given missed detection rate. We also show that a GLRT detector composed of a few high-rank subspace detectors has a slightly higher nontarget detection rate, but a significantly lower missed detection rate, than a GLRT detector composed of many low-rank subspace detectors. The high-rank GLRT configuration produced impressive results even with marginal data (single channel, single station, and very low time bandwidth product), which bodes well for the utility of building efficient aftershock classification systems and global monitoring systems at larger scales. However, future work is required to assess performance at the regional scale and to assess the performance of the system at detecting target events not used in the detector template creation.

58 GEOSCIENCES↗