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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 37 records · Page 2

Applying Corrective Machine Learning in the E3SM Atmosphere Model in C++ (EAMxx)

The Simplified Cloud-Resolving E3SM Atmosphere Model (SCREAM) is the newest addition to the family of Earth System Models capable of explicitly resolving convective systems. SCREAM is a kilometer-scale configuration of the advanced E3SM Atmosphere Model (EAMxx), designed for heterogeneous systems. While the enhanced accuracy of kilometer-scale modeling offers significant benefits, it comes with a substantial computational cost, limiting feasible simulation durations to only a few years, even on the fastest supercomputers. Machine learning presents an opportunity for scientists to achieve the high accuracy of storm-resolving models at a significantly reduced cost. Building on the previous success of applying corrective machine learning (ML) to the FV3 model, this study explores the effects of implementing corrective ML in EAMxx-SCREAM. We also address the computational challenges of integrating the corrective ML, which is written in Python, with the C++/Kokkos EAMxx driver, as well as the potential pitfalls of generalizing an approach that was effective with one atmosphere model to another.

54 ENVIRONMENTAL SCIENCES↗

Deep Reinforcement Learning for Resilient Power and Energy Systems: Progress, Prospects, and Future Avenues

In recent years, deep reinforcement learning (DRL) has garnered substantial attention in the context of enhancing resilience in power and energy systems. Resilience, characterized by the ability to withstand, absorb, and quickly recover from natural disasters and human-induced disruptions, has become paramount in ensuring the stability and dependability of critical infrastructure. This comprehensive review delves into the latest advancements and applications of DRL in enhancing the resilience of power and energy systems, highlighting significant contributions and key insights. The exploration commences with a concise elucidation of the fundamental principles of DRL, highlighting the intricate interplay among reinforcement learning (RL), deep learning, and the emergence of DRL. Furthermore, it categorizes and describes various DRL algorithms, laying a robust foundation for comprehending the applicability of DRL. The linkage between DRL and power system resilience is forged through a systematic classification of DRL applications into five pivotal dimensions: dynamic response, recovery and restoration, energy management and control, communications and cybersecurity, and resilience planning and metrics development. This structured categorization facilitates a methodical exploration of how DRL methodologies can effectively tackle critical challenges within the domain of power and energy system resilience. The review meticulously examines the inherent challenges and limitations entailed in integrating DRL into power and energy system resilience, shedding light on practical challenges and potential pitfalls. Additionally, it offers insights into promising avenues for future research, with the aim of inspiring innovative solutions and further progress in this vital domain.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Deep anomaly detection for industrial systems: a case study

We explore the use of deep neural networks for anomaly detection of industrial systems where the data are multivariate time series measurements. We formulate the problem as a self-supervised learning where data under normal operation are used to train a deep neural network autoregressive model, i.e., use a window of time series data to predict future data values. The aim of such a model is to learn to represent the system dynamic behavior under normal conditions, while expect higher model vs. measurement discrepancies under faulty conditions. In real world applications, many control settings are discrete in nature. In this paper, vector embedding and joint losses are employed to deal with such situations. Both LSTM and CNN based deep neural network backbones are studied on the Secure Water Treatment (SWaT) testbed datasets. Also, Support Vector Data Description (SVDD) method is adapted to such anomaly detection settings with deep neural networks. Evaluation methods and results are discussed based on the SWaT dataset along with potential pitfalls.

anomaly detection, deep neural network↗

Investigating Bacterial-Fungal Interactions using Fungal Highway Columns in Diverse Environments and Substrates

Bacterial-fungal interactions (BFIs) play an integral role in shaping microbial community composition, biogeochemical functions, spatial dynamics, and microbial dispersal. Mycelial networks created by filamentous fungi or other filamentous microorganisms (e.g., Oomycetes) act as 'fungal highways' that can be utilized by bacteria for transport throughout heterogeneous environments, greatly facilitating their mobility and granting them access to regions that may be challenging or impossible to reach on their own (e.g., due to air pockets within the soil). Several devices and experimental protocols have been created to study these fungal highways, including fungal highway columns. The fungal highway column designed by our group can be used for a variety of in situ or in vitro applications, as well as with diverse environmental and host-associated sample types. Herein, we describe the methods for performing experiments with these columns, including designing, printing, sterilizing, and preparing the devices. The options for analyzing data obtained from the use of these devices are also discussed here, and troubleshooting advice regarding potential pitfalls associated with experiments using fungal highway columns is offered. These devices can be used to gain a more comprehensive understanding of the diversity, mechanisms, and dynamics of fungal highway BFIs to provide valuable insights into the structural and functional dynamics within complex environments (e.g., soils) and across diverse habitats in which bacteria and fungi co-exist.

59 BASIC BIOLOGICAL SCIENCES↗

Using neural network ensembles to separate ocean biogeochemical and physical drivers of phytoplankton biogeography in Earth system models

Abstract. Earth system models (ESMs) are useful tools for predicting and understanding past and future aspects of the climate system. However, the biological and physical parameters used in ESMs can have wide variations in their estimates. Even small changes in these parameters can yield unexpected results without a clear explanation of how a particular outcome was reached. The standard method for estimating ESM sensitivity is to compare spatiotemporal distributions of variables from different runs of a single ESM. However, a potential pitfall of this method is that ESM output could match observational patterns because of compensating errors. For example, if a model predicts overly weak upwelling and low nutrient concentrations, it might compensate for this by allowing phytoplankton to have a high sensitivity to nutrients. Recently, we demonstrated that neural network ensembles (NNEs) are capable of extracting relationships between predictor and target variables within ocean biogeochemical models. Being able to view the relationships between variables, along with spatiotemporal distributions, allows for a more mechanistically based examination of ESM outputs. Here, we investigated whether we could apply NNEs to help us determine why different ESMs produce different spatiotemporal distributions of phytoplankton biomass. We tested this using three cases. The first and second case used different runs of the same ESM, except that the physical circulations differed between them in the first case, while the biological equations differed between them in the second. Our results indicated that the NNEs were capable of extracting the relationships between variables for different runs of a single ESM, allowing us to distinguish between differences due to changes in circulation (which do not change relationships) from changes in biogeochemical formulation (which do change relationships). In the third case, we applied NNEs to two different ESMs. The results of the third case highlighted the capability of NNEs to contrast the apparent relationships of different ESMs and some of the challenges it presents. Although applied specifically to the ocean components of an ESM, our study demonstrates that Earth system modelers can use NNEs to separate the contributions of different components of ESMs. Specifically, this allows modelers to compare the apparent relationships across different ESMs and observational datasets.

54 ENVIRONMENTAL SCIENCES↗

The Use of Self-scanned Silicon Photodiode Arrays for Astronomical Spectrophotometry

The use of a Reticon self scanned silicon photodiode array for precision spectrophotometry is discussed. It is shown that internal errors are + or - 0.003 mag. Observations obtained with a photodiode array are compared with observations obtained with other types of detectors with agreement, from 3500 A to 10500 A, of 1%. The photometric properties of self scanned photodiode arrays are discussed. Potential pitfalls are given.

Cochran, A. L.↗

Thin-film module circuit design: Practical and reliability aspects

This paper will address several aspects of the design and construction of submodules based on thin film amorphous silicon (a-Si) p i n solar cells. Starting from presently attainable single cell characteristics, and a realistic set of specifications, practical module designs are discussed from the viewpoints of efficient designs, the fabrication requirements, and reliability concerns. The examples center mostly on series interconnected modules of the superstrate type with detailed discussions of each portion of the structure in relation to its influence on module efficiency. Emphasis is placed on engineering topics such as: area coverage, optimal geometries, and cost and reliability. Practical constraints on achieving optimal designs, along with some examples of potential pitfalls in the manufacture and subsequent performance of a-Si modules are discussed.

Daiello, R. V.↗

Comments on the challenge of using mesoscale data in mesoscale numerical models

The dangers of addressing the initialization issues for limited-area mesoscale models by extending the lessons learned during the development of global analysis and prediction systems are discussed. Lack of impact with data inserts at one time suggests that the lateral boundary conditions imposed on the limited-area models might force the model simulation toward a preferred solution, work against the new data being inserted into the model and, therefore, limit the potential impact that this data can have on the model system. The second potential pitfall involves the imposition of balance constraints on the data that are being inserted into the model to compute winds from temperature data and/or temperature from wind data.

Uccellini, Louis W.↗

An analytic development of orbit determination for a distant, planetary orbiter

With the advent of the Mariner '71 Mission, NASA has been sending spacecraft to orbit various distant bodies within the solar system. At present, there is still no adequate theory describing the inherent state estimation accuracy, based on two-way, coherent range-rate data. It is the purpose of this article to lay the groundwork for a general elliptic theory, and in addition to provide an analytic solution for the special case of circular orbits. It is shown that circular orbits about distant planets may suffer singularities in over-all position error estimation. These singularities are due to orbit inclination, placement of the line-of-nodes, and insignificant cross-velocity at the start and end of retrograde motion when orbiting a superior planet. Even though these conclusions appear to yield poor state estimation, one should not be unduly alarmed inasmuch as the stated conditions for singularity are not maintained for extended periods during typical mission scenarios. However, mission analysts should be aware of these potential pitfalls and realize that spuriously large results for circular orbiters can be obtained and are not the result of incorrect assumptions or faulty software. The general elliptic problem appears so involved that analytic inversion at this time is just not feasible, and in any case the resulting expression for the position error would likely be so lengthy that any understanding would be lost in the maze.

Russell, R. K.↗

High-resolution seismic reflection survey at the Manson crater, Iowa

Approximately 17.4 km of high-resolution reflection data were acquired along an east-west radius of the Manson Impact Structure (MIS) to delineate the shallow (upper 300 m) subsurface structural configuration. The geometry of the shallow structure is poorly known due to a 30-90 m thick Pleistocene till cover. The resolution of the new seismic data is roughly 5-10 times that of existing Vibroseis data. Data quality varies rapidly along the line from exceptional to poor, due primarily to velocity variations associated with the geological complexity of the area. Preliminary results indicate subsurface structural blocks previously envisioned to be several hundreds of meters in size are actually an order of magnitude smaller and more complex. A seismogram-by-seismogram analysis is necessary to confidently identify intricate stratigraphic and structural relationships seen on preliminary CDP sections, as numerous faults, diffractions, and complicated reflection patterns create potential pitfalls.

Keiswetter, D. A.↗

Baseline tests of an autonomous telerobotic system for assembly of space truss structures

Several proposed space missions include precision reflectors that are larger in diameter than any current or proposed launch vehicle. Most of these reflectors will require a truss structure to accurately position the reflector panels and these reflectors will likely require assembly in orbit. A research program has been conducted at the NASA Langley Research Center to develop the technology required for the robotic assembly of truss structures. The focus of this research has been on hardware concepts, computer software control systems, and operator interfaces necessary to perform supervised autonomous assembly. A special facility was developed and four assembly and disassembly tests of a 102-strut tetrahedral truss have been conducted. The test procedures were developed around traditional 'pick-and-place' robotic techniques that rely on positioning repeatability for successful operation. The data from two of the four tests were evaluated and are presented in this report. All operations in the tests were controlled by predefined sequences stored in a command file, and the operator intervened only when the system paused because of the failure of an actuator command. The tests were successful in identifying potential pitfalls in a telerobotic system, many of which would not have been readily anticipated or incurred through simulation studies. Addressing the total integrated task, instead of bench testing the component parts, forced all aspects of the task to be evaluated. Although the test results indicate that additional developments should be pursued, no problems were encountered that would preclude automated assembly in space as a viable construction method.

Rhodes, Marvin D.↗

Athena: Advanced air launched space booster

The infrastructure for routine, reliable, and inexpensive access of space is a goal that has been actively pursued over the past 50 years, but has yet not been realized. Current launch systems utilize ground launching facilities which require the booster vehicle to plow up through the dense lower atmosphere before reaching space. An air launched system on the other hand has the advantage of being launched from a carrier aircraft above this dense portion of the atmosphere and hence can be smaller and lighter compared to its ground based counterpart. The goal of last year's Aerospace Engineering Course 483 (AE 483) was to design a 227,272 kg (500,000 lb.) air launched space booster which would beat the customer's launch cost on existing launch vehicles by at least 50 percent. While the cost analysis conducted by the class showed that this goal could be met, the cost and size of the carrier aircraft make it appear dubious that any private company would be willing to invest in such a project. To avoid this potential pitfall, this year's AE 483 class was to design as large an air launched space booster as possible which can be launched from an existing or modification to an existing aircraft. An initial estimate of the weight of the booster is 136,363 kg (300,000 lb.) to 159,091 kg (350,000 lb.).

Booker, Corey G.↗

Aerodynamic and Aeroelastic Insights using Eigenanalysis

This paper presents novel analytical results for eigenvalues and eigenvectors produced using discrete time aerodynamic and aeroelastic models. An unsteady, incompressible vortex lattice aerodynamic model is formulated in discrete time; the importance of several modeling parameters is examined. A detailed study is made of the behavior of the aerodynamic eigenvalues both in discrete and continuous time. The aerodynamic model is then incorporated into aeroelastic equations of motion. Eigenanalyses of the coupled equations produce stability results and modal characteristics which are valid for critical and non-critical velocities. Insight into the modeling and physics associated with aeroelastic system behavior is gained by examining both the eigenvalues and the eigenvectors. Potential pitfalls in discrete time model construction and analysis are examined.

Heeg, Jennifer↗

Logic Design Pathology and Space Flight Electronics

Logic design errors have been observed in space flight missions and the final stages of ground test. The technologies used by designers and their design/analysis methodologies will be analyzed. This will give insight to the root causes of the failures. These technologies include discrete integrated circuit based systems, systems based on field and mask programmable logic, and the use computer aided engineering (CAE) systems. State-of-the-art (SOTA) design tools and methodologies will be analyzed with respect to high-reliability spacecraft design and potential pitfalls are discussed. Case studies of faults from large expensive programs to "smaller, faster, cheaper" missions will be used to explore the fundamental reasons for logic design problems.

Katz, Richard↗

Determination of Highly Accurate Heats of Formation

Two approaches for directly computing a molecular heat of formation based on sophisticated ab initio electronic structure theory axe discussed and example calculations are presented for several molecules of interest in atmospheric chemistry including HNO and CICN. The accuracy of these approaches for a small subset of the molecules is demonstrated by comparison to very accurate experimental data. A third approach for evaluating accurate heats of formation consists of combining experimental and theoretical data. The potential for this method to provide reliable thermochemical data on many molecules using accurate experimental beats of formation for only a small number of species is demonstrated by giving accurate (Delta)H(sup 0, sub f) quantities for a host of fluorine, chlorine, and bromine oxide and nitrogen oxide compounds. Potential pitfalls in all three approaches are discussed.

Lee, Timothy J.↗

Lessons Learned (3 Years of H2O2 Propulsion System Testing Efforts at NASA's John C. Stennis Space Center)

John C. Stennis Space Center continues to support the Propulsion community in an effort to validate High-Test Peroxide as an alternative to existing/future oxidizers. This continued volume of peroxide test/handling activity at Stennis Space Center (SSC) provides numerous opportunities for the SSC team to build upon previously documented 'lessons learned'. SSC shall continue to strive to document their experience and findings as H2O2 issues surface. This paper is intended to capture all significant peroxide issues that we have learned over the last three years. This data (lessons learned) has been formulated from practical handling, usage, storage, operations, and initial development/design of our systems/facility viewpoint. The paper is intended to be an information type tool and limited in technical rational; therefore, presenting the peroxide community with some issues to think about as the continued interest in peroxide evolves and more facilities/hardware are built. These lessons learned are intended to assist industry in mitigating problems and identifying potential pitfalls when dealing with the requirements for handling high-test peroxide.

Taylor, Gary O.↗

Aerodynamic and Aeroelastic Insights using Eigenanalysis

This paper presents novel analytical results for eigenvalues and eigenvectors produced using discrete time aerodynamic and aeroelastic models. An unsteady, incompressible vortex lattice aerodynamic model is formulated in discrete time; the importance of several modeling parameters is examined. A detailed study is made of the behavior of the aerodynamic eigenvalues both in discrete and continuous time. The aerodynamic model is then incorporated into aeroelastic equations of motion. Eigenanalyses of the coupled equations produce stability results and modal characteristics which are valid for critical and non-critical velocities. Insight into the modeling and physics associated with aeroelastic system behavior is gained by examining both the eigenvalues and the eigenvectors. Potential pitfalls in discrete time model construction and analysis are examined.

Heeg, Jennifer↗

Quantifying Exact Motions Along Lineaments on Europa

Evaluating the precise motions along lineaments on the surface of Jupiter's icy moon, Europa, is a valuable tool for interpreting the development and history of lineaments of various morphologies. Such morphologies include strike-slip faults, dilational bands, ridges, and convergence zones. However, the exact mode of origin and kinematic behavior of these various lineaments are not obvious based on morphology alone. In fact, the apparent motions implied by displaced crosscut features can provide misleading indications of true motions along lineaments. Identifying the precise motions (combinations of sliding and opening/closing) is critical to the accurate characterization and interpretation of each of these lineament types. Lineaments of interest (i.e., those having displaced relatively older features in some manner) are identified on Galileo spacecraft images and measurements are made of the total offset, the separation, and relative orientations of crosscut features with respect to the lineament of interest. Specifically, by using these measured quantities and a series of trigonometric equations, the precise motions (i.e., dilation, convergence, strike-slip, or a combination of strike-slip and dilation or convergence) can be determined. These measurements are, however, limited by the resolution of the available images. This study focuses on motion analysis techniques for Europan lineaments and the precise characterization of fault-orthogonal and/or strike-slip motion along lineaments of varying morphologies. We highlight potential pitfalls of cursory analyses of motion indicators. For example, lineaments with obvious lateral offsets have typically been identified simply as strike-slip faults. This assumption may actually be incorrect, as fault-orthogonal motions may contribute to apparent lateral displacements (offsets or separations). Also, variability in the amount of fault motion along the trace length should theoretically be identifiable using the outlined technique. Strike-slip faults on Europa have conventionally been presumed to have a constant slip magnitude along their lengths; however, we posit that variable distributions of slip may be common, as is typical along terrestrial strike-slip faults.

Vetter, J. C.↗