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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Photovoltaic Analysis and Response Support (PARS) Platform for Solar Situational Awareness and Resiliency Services

The project's primary objective is to develop a digital-twin based Photovoltaic (PV) Analysis and Response Support (PARS) platform, which aims to provide real-time situational awareness and optimal response plans. This platform is designed to enhance the performance of hybrid PV systems, making them competitive with or even superior to conventional generation resources. The PARS platform enabled the project team to develop and evaluate an extensive suite of grid support functionalities for the hybrid PV systems to enhance grid performance, across key areas including visibility, dispatchability, security, resilience, and reliability. Given the global push toward achieving 100% clean energy by 2035, there is a significant increase in the integration of inverter-based resources (IBRs) throughout the energy grid. Effectively managing the inherent variability and uncertainty associated with IBRs is crucial for ensuring cost-effectiveness, reliability, and security in both the main grid and islanded microgrids. Constrained to a limited array of IEEE test systems or standard feeder models, traditional IBR modeling struggles to assimilate new field data, accurately reflect system dynamics, and adapt to the evolving energy landscape. In our project, we embraced a Digital Twin (DT) strategy for crafting the PARS platform. A digital twin acts as a precise virtual counterpart of a physical system, built on historical data and continuously honed with real-time insights. This enables the high-fidelity DT to accurately mirror current system operations and forecast future scenarios. Consequently, the PARS platform becomes an ideal environment for testing and refining monitoring, control, power, and energy management algorithms designed to boost hybrid PV system performance. The defining feature of the PARS platform, distinguishing it from other advanced simulation tools, is its exceptional adaptability. This is achieved by employing actual network topologies and utilizing real-time field data for fine-tuning and calibration, ensuring a close emulation of real-world conditions. The project deliverables include: 1) High-fidelity IBR models and tools for real-time parameterization, utilizing real-time field measurements to refine IBR models for enhanced accuracy and performance; 2) Grid-forming and Grid-following capabilities to deliver resilience services, including blackstart, voltage and frequency support, cold-load pick-up, power reserves, and three-phase load balancing across grid-connected and microgrid settings; 3) Machine learning-based forecasting tools and methods for generating synthetic data and topologies, creating diverse and realistic simulation environments for evaluating varied operational scenarios; 4) Advanced microgrid power and energy management algorithms for optimizing the integration and operation of PV, storage, and demand response resources within both feeder and community scales. The power grid data sets are provided by four utility companies in North Carolina and the New York Power Administration. Acting as industry advisors, our industry partners communicated stakeholder needs and regulatory standards to the research teams, aiding technology transfer by incorporating the developed methodologies into their daily operations. This collaboration ensures that the PARS platform, functioning as a power system digital twin, enhances our understanding of IBR dynamic behaviors and enables the development and evaluation of IBR control functions that match or exceed the capabilities of conventional synchronous generators.

14 SOLAR ENERGY↗
NASA NTRS2021

3D Simulations of the Early Martian Hydrological Cycle Mediated by a H2-CO2 Greenhouse

For decades, the scientific community has been trying to reconcile abundant evidence for fluvialactivity on Noachian and early Hesperian Mars with the faint young Sun and reasonableconstraints on ancient atmospheric pressure and composition. Recently, the investigation of H2-CO2 collision-induced absorption has opened up a new avenue to warm Noachian Mars. We usethe ROCKE-3D global climate model to simulate plausible states of the ancient Martian climatewith this absorptive warming and reasonable constraints on surface paleopressure. We find that1.5-2 bar CO2-dominated atmospheres with ≥3% H2 can produce global mean surfacetemperatures above freezing, while also providing sufficient warming to avoid surfaceatmospheric CO2 condensation at 0°-45° obliquity. Simulations conducted with both moderntopography and a paleotopography, before Tharsis formed, highlight the importance of Tharsis asa cold trap for water on the planet. Additionally, we find that low obliquity (modern and 0°) ismore conducive to rainfall over valley network locations than high (45°) obliquity. PLAIN LANGUAGE SUMMARY Much evidence tells us that ancient Mars had liquid water on its surface. But reconciling thatwith the fainter young Sun and reasonable constraints on Mars' early atmosphere is challenging.We use a 3D global climate model with an atmosphere containing some amount of hydrogen (apossible greenhouse gas) to study Mars' early hydrological cycle and compare it to the geologicalevidence of surface liquid water billions of years ago. We find that hydrogen and carbon dioxidetogether in an atmosphere twice as thick as modern Earth can warm early Mars above thefreezing point of water and that a low axial tilt produces rainfall patterns that best match thegeologic evidence

Scott D Guzewich↗
NASA NTRSDate not supplied

FAIR-ness Assessment of NASA’s Earth Observation System Data and Information System (EOSDIS)

This presentation addresses the challenge of evaluating a multi-disciplinary institutional network of data repositories in operation since 1994 against the relatively recent criteria that constitute FAIR (Findable, Accessible, Interoperable, Reusable) data. NASA’s Earth Observation System Data and Information System (EOSDIS), with its 12 discipline-based Distributed Active Archive Centers (DAACs), preceded the definition and popularization of FAIR by over two decades. An assessment is very useful to describe how well the FAIR principles are met and to identify any improvements needed. In 2020, A “self-assessment” of EOSDIS and DAACs was performed by the ESDIS Project staff and the DAACs from the points of view of human actionability and machine actionability. More recently, a draft of a Science Mission Directorate (SMP) Program Directive (SPD-41a) has been released by NASA Headquarters for comment, where it is recommended that all SMD-funded data should follow the FAIR principles. This presentation is timely to initiate community discussion within the Information Quality Cluster (IQC) of the Earth Science Information Partners (ESIP) and help strategize and develop implementation guidelines for EOSDIS and DAACs to conform to FAIR principles.

Remote sensing↗
NASA NTRS2012

Asthma and Air Quality in the Presence of Fires - A Foundation for Public Health Policy in Florida

Outdoor air quality and its associated impacts on respiratory problems in Florida are of public health significance. Air quality in Florida can be poor during the extended wildfire season, threatening persons with compromised respiratory systems each year. Studies have demonstrated that particulate matter, which is generally elevated in the vicinity of wildfires, is associated with increases in hospital admissions and occurrences of acute asthma exacerbations. However, few studies have examined the modifying effect of socio-demographic characteristics of cities or regional areas on the relationship between air quality and health outcomes. In an ongoing university/multi-agency project, asthma hospital/emergency room (patient) data are being used to create a health outcome indicator of human response to environmental air quality. Environmental data are derived from satellite measurements, with special attention being given to the effect of wildfires and prescribed burns on air quality. This presentation will focus on the environmental data sets particulate matter, location of fires, smoke plumes that are being collected and processed for linkage with health data. After this linkage has been performed, space-time models of asthma rates as a function of air quality data and socio-demographic variables will be developed and validated. The Florida Department of Health (FDOH) will work with county health department staff and representatives from the medical community to establish a protocol with triggers for issuing public health advisories/alerts based on the developed and validated health outcome indicators. From this effort, a science-based policy for issuing public health advisories/alerts for asthma relating to air quality will be developed, giving FDOH the ability to (1) predict, with stated levels of uncertainty, case load of hospital admissions based on air quality, (2) reduce asthma exacerbations by forewarning asthmatics to limit outside activities on poor air quality days, (3) apply management practices on the rates of hospital/emergency room visits for asthma, and (4) provide information that would help translate interventions into policy decisions, thereby reducing the economic burden and increasing well being of asthmatics. Further, the results of the study will be incorporated into Florida s Environmental Public Health Tracking (EPHT) program, which is part of the Centers for Disease Control and Prevention's (CDC's) EPHT network.

Crosson, William↗
DOE OSTI2025

Mesoscale Cellular Convection Detection and Classification Using Convolutional Neural Networks: Insights From Long-Term Observations at ARM Eastern North Atlantic Site

Marine boundary layer clouds are crucial in Earth's climate system. They frequently manifest as closed or open cell mesoscale cellular convection (MCC). MCC clouds are challenging to represent accurately in current climate models, highlighting the need for detailed observational data sets and in-depth analyses. This study utilizes over 8 years of observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility Eastern North Atlantic (ENA) site at Graciosa Island, Azores, to investigate these clouds. We first apply a convolutional neural network with a U-Net architecture to classify open and closed cells, marking the first application of such an approach for automatically detecting MCC patterns from ground-based radar measurements. This method addresses some observational gaps in satellite data related to low temporal resolution, nighttime challenges, and limited vertical structure capture. The analysis of the MCC cases shows clear differences between closed and open MCCs: Closed MCC clouds are characterized by lower cloud tops and bases, shallower cloud geometrical depth, weaker horizontal wind speeds, stronger atmospheric stability, and a more homogeneous liquid water path than open MCCs. Finally, we demonstrate two potential applications of our radar-based MCC classifications: (a) facilitating the investigation of aerosol-cloud interactions and (b) exploring meteorological factors along with MCC's evolution by integrating satellite imagery and back-trajectory analysis. The identified MCC cases offer a valuable resource for the scientific community to study MCC processes further and improve climate model accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Ecosystem-Level Biomimicry for the Built Environment: Adopting Systems Ecology Principles for the Control of Heterogeneous Energy Systems

This paper presents, to our knowledge, the first system-level engineering study to bio-mimic the cybernetics and flow dynamics of energy resources in natural ecosystems for the control of heterogeneous energy infrastructures in the built environment. To this end, we introduce a novel Biomimetic Pulsing State (BPS) control that functionally mimics mature ecosystems. A preliminary Modelica-based case study features a single-family residential building with electrical and HVAC subsystems. The BPS control objective is to minimize the energy exchange between the building and the grid for the purposes of future self-supporting buildings and grid stability. The building contains PV, a wind turbine, a battery storage system, and a fan coil/heat pump HVAC system served by an ambient district energy network. Evaluating the control performance (BPS vs. constant setpoint) over several renewable energy scenarios (net importer, net zero, net exporter), simulation results show how the building's HVAC system can dynamically adjust its electrical load and temperatures to the electrical system's net energy status in real-time with BPS control. As a net importer, the heat pump consumed 29% less energy and its peak power reduced by 15% with BPS control compared to the constant setpoint case, with the zone air temperature 1 degree C lower on average. As a net exporter, the heat pump effectively consumed the same energy, but the peak power increased by 34% with BPS control, while the zone air temperature was 1 degree C higher when renewable energy was abundant, preheating the home. BPS and constant setpoint control produced comparable results under a net zero scenario. While further evaluation is essential, BPS control may help communities meet their sustainability and resiliency targets as they transition towards fully distributed and renewable energy grids.

biomimicry↗
NASA NTRS2015

Global Precipitation Measurement Cold Season Precipitation Experiment (GCPEx): For Measurement Sake Let it Snow

As a component of the Earth's hydrologic cycle, and especially at higher latitudes,falling snow creates snow pack accumulation that in turn provides a large proportion of the fresh water resources required by many communities throughout the world. To assess the relationships between remotely sensed snow measurements with in situ measurements, a winter field project, termed the Global Precipitation Measurement (GPM) mission Cold Season Precipitation Experiment (GCPEx), was carried out in the winter of 2011-2012 in Ontario, Canada. Its goal was to provide information on the precipitation microphysics and processes associated with cold season precipitation to support GPM snowfall retrieval algorithms that make use of a dual-frequency precipitation radar and a passive microwave imager on board the GPM core satellite,and radiometers on constellation member satellites. Multi-parameter methods are required to be able to relate changes in the microphysical character of the snow to measureable parameters from which precipitation detection and estimation can be based. The data collection strategy was coordinated, stacked, high-altitude and in-situ cloud aircraft missions with three research aircraft sampling within a broader surface network of five ground sites taking in-situ and volumetric observations. During the field campaign 25 events were identified and classified according to their varied precipitation type, synoptic context, and precipitation amount. Herein, the GCPEx fieldcampaign is described and three illustrative cases detailed.

GCPEx↗
DOE OSTI2026

Citation network datasets for benchmarking spiking graph neural networks on experimental neuromorphic hardware

Spiking neural networks (SNNs) running on neuromorphic computers offer an energy-efficient alternative for AI tasks. Recently, spiking graph neural networks (S-GNNs) have been shown to produce encouraging results on benchmark citation network datasets such as Cora, CiteSeer, and PubMed for node classification tasks. These S-GNNs were run on SNN simulators only because they contain up to tens of thousands of neurons and up to millions of synapses, translating poorly to neuromorphic hardware. Therefore, in this paper, we create a suite of benchmark datasets from the CiteSeer dataset that can be accommodated on current neuromorphic hardware platforms. Our contribution consists of a collection of three datasets. First, we have an induced subgraph of CiteSeer, which we call MiniSeer, containing 2110 papers, 3604 binary features, and 6 topics. Second, MicroSeer is a very small dataset consisting of 84 papers, 1227 features, and 6 topics. Lastly, BiteSeer is a collection of 15 binary classification datasets. We present creation of these datasets along with accuracies, running times, and spike counts when simulated. We believe that our results in this paper will be used by the neuromorphic community to benchmark, test, and develop neuromorphic hardware and simulators.

Zhu, Kevin [George Mason University, Virginia]↗
NASA NTRS2014

Using SpF to Achieve Petascale for Legacy Pseudospectral Applications

Pseudospectral (PS) methods possess a number of characteristics (e.g., efficiency, accuracy, natural boundary conditions) that are extremely desirable for dynamo models. Unfortunately, dynamo models based upon PS methods face a number of daunting challenges, which include exposing additional parallelism, leveraging hardware accelerators, exploiting hybrid parallelism, and improving the scalability of global memory transposes. Although these issues are a concern for most models, solutions for PS methods tend to require far more pervasive changes to underlying data and control structures. Further, improvements in performance in one model are difficult to transfer to other models, resulting in significant duplication of effort across the research community. We have developed an extensible software framework for pseudospectral methods called SpF that is intended to enable extreme scalability and optimal performance. Highlevel abstractions provided by SpF unburden applications of the responsibility of managing domain decomposition and load balance while reducing the changes in code required to adapt to new computing architectures. The key design concept in SpF is that each phase of the numerical calculation is partitioned into disjoint numerical kernels that can be performed entirely inprocessor. The granularity of domain decomposition provided by SpF is only constrained by the datalocality requirements of these kernels. SpF builds on top of optimized vendor libraries for common numerical operations such as transforms, matrix solvers, etc., but can also be configured to use open source alternatives for portability. SpF includes several alternative schemes for global data redistribution and is expected to serve as an ideal testbed for further research into optimal approaches for different network architectures. In this presentation, we will describe our experience in porting legacy pseudospectral models, MoSST and DYNAMO, to use SpF as well as present preliminary performance results provided by the improved scalability.

DYNAMO↗
NASA NTRS2008

Optical Communications from Planetary Distances

Future planetary campaigns, including human missions, will require data rates difficult to realize by microwave links. Optical channels not only provide an abundance of bandwidth, they also allow for significant size, weight, and power reduction. Moreover, optical-based tracking may enhance spacecraft navigation with respect to microwave-based tracking. With all its advantages, optical communications from deep space is not without its challenges. Due to the extreme distance between the two ends of the link, specialized technologies are needed to enable communications in the deep space environment. Although some of the relevant technologies have been developed in the last decade, they remain to be validated in an appropriate domain. The required assets include efficient pulsed laser sources, modulators, transmitters, receivers, detectors, channel encoders, precise beam pointing technologies for the flight transceiver and large apertures for the ground receiver. Clearly, space qualification is required for the systems that are installed on a deep space probe. Another challenge is atmospheric effects on the optical beam. Typical candidate locations on the ground have a cloud-free line of sight only on the order of 60-70% of the time. Furthermore, atmospheric losses and background light can be problematic even during cloud-free periods. Lastly, operational methodologies are needed for efficient and cost effective management of optical links. For more than a decade, the National Aeronautics and Space Administration (NASA) has invested in relevant technologies and procedures to enable deep space optical communications capable of providing robust links with rates in the order of 1 Gb/s from Mars distance. A recent publication indicates that potential exists for 30-dB improvement in performance through technology development with respect to the state-of-the-art in the early years of this decade. The goal is to fulfill the deep space community needs from about 2020 to the foreseeable future. It is envisioned that, at least initially, optical links will be complemented by microwave assets for added robustness, especially for human missions. However, it is expected that as optical techniques mature, laser communications may be operated without conventional radio frequency links. The purpose of this paper is to briefly review the state-of-the-art in deep space laser communications and its challenges and discuss NASA-supported technology development efforts and plans for deep space optical communications at JPL.

Laser Communications↗
DOE OSTI2020

The updated DESGW processing pipeline for the third LIGO/VIRGO observing run

The DESGW group seeks to identify electromagnetic counterpartsof gravitational wave events seen by the LIGO-VIRGO network, such as thoseexpected from binary neutron star mergers or neutron star- black hole mergers.DESGW was active throughout the first two LIGO observing seasons, followingup several binary black hole mergers and the first binary neutron star merger,GW170817. We describe the modifications to the observing strategy generationand image processing pipeline between the second (ending in August 2017)and third (beginning in April 2019) LIGO observing seasons. The modifica-tions include a more robust observing strategy generator, further parallelizationof the image reduction software and dierence imaging processing pipeline,data transfer streamlining, and a web page listing identified counterpart candi-dates that updates in real time. Taken together, the additional parallelizationsteps enable us to identify potential electromagnetic counterparts within fullycalibrated search images in less than one hour, compared to the 3-5 hours itwould typically take during the first two seasons. These performance improve-ments are critical to the entire EM followup community, as rapid identification(or rejection) of candidates enables detailed spectroscopic followup by multipleinstruments as soon as possible, leading to more information about the environ-ment immediately following such gravitational wave events.

Herner, Kenneth R.↗
DOE OSTI2024

Scalar bounded-from-below conditions from Bayesian active learning

We present a procedure leveraging Bayesian deep active learning to rapidly produce highly accurate approximate bounded-from-below conditions for arbitrary renormalizable scalar potentials, in the form of a neural network which may be saved and exported for use in arbitrary parameter space scans. We explore the performance of our procedure on three different scalar potentials with either highly nontrivial or unknown symbolic bounded-from-below conditions (the most general two-Higgs doublet model, the three-Higgs doublet model, and a version of the Georgi-Machacek model without custodial symmetry). We find that we can produce fast and highly accurate binary classifiers for all three potentials. Furthermore, for the potentials for which no known symbolic necessary and sufficient conditions on boundedness-from-below exist, our classifiers substantially outperform some common approximate analytical methods, such as producing tractable sufficient but not necessary conditions or evaluating boundedness-from-below conditions for scenarios in which only a subset of the theory’s fields achieve vacuum expectation values. Our methodology can be readily adapted to any renormalizable scalar field theory. For the community’s use, we have developed a package, BFBrain, which allows for the rapid implementation of our analysis procedure on user-specified scalar potentials with a high degree of customizability. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2026

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗
NASA NTRS1993

Adaptive digital beamforming for a CDMA mobile communications payload

In recent years, Spread-Spectrum Code Division Multiple Access (CDMA) has become a very popular access scheme for mobile communications due to a variety of reasons: excellent performance in multipath environments, high scope for frequency reuse, graceful degradation near saturation, etc. In this way, a CDMA system can support simultaneous digital communication among a large community of relatively uncoordinated users sharing a given frequency band. Nevertheless, there are also important problems associated with the use of CDMA. First, in a conventional CDMA scheme, the signature sequences of asynchronous users are not orthogonal and, as the number of active users increases, the self-noise generated by the mutual interference between users considerably degrades the performance, particularly in the return link. Furthermore, when there is a large disparity in received powers - due to differences in slant range or atmospheric attenuation - the non-zero cross-correlation between the signals gives rise to the so-called near-far problem. This leads to an inefficient utilization of the satellite resources and, consequently, to a drastic reduction in capacity. Several techniques were proposed to overcome this problem, such as Synchronized CDMA - in which the signature sequences of the different users are quasi-orthogonal - and power control. At the expense of increased network complexity and user coordination, these techniques enable the system capacity to be restored by equitably sharing the satellite resources among the users. An alternative solution is presented based upon the use of time-reference adaptive digital beamforming on board the satellite. This technique enables a high number of independently steered beams to be generated from a single phased array antenna, which automatically track the desired user signal and null the unwanted interference source. In order to use a time-reference adaptive antenna in a communications system, the main challenge is to obtain a reference signal highly correlated with the desired user signal and uncorrelated with the interferences. CDMA lends itself very easily to the generation of such a reference signal, thanks to the a priori knowledge of the user's signature sequence. First, the integration of an adaptive antenna in an asynchronous CDMA system is analyzed. The adaptive antenna system can provide increased interference rejection - much higher than that afforded by the code alone - and, since CDMA is mainly interference limited, any reduction in interference converts directly and linearly into an increase in capacity. Analyses and computer simulations are presented that show how an asynchronous CDMA system incorporating adaptive beamforming can provide at least as much capacity as a synchronous system. More importantly, the proposed concept allows the near-far effect to be mitigated without requiring a tight coordination of the users in terms of transmitted power control or network synchronization. The system is extremely robust to the near-far effect because the signals reaching the satellite from directions other than that of the desired user - which are likely to have different power levels - are adaptively canceled by the antenna. Finally, a payload architecture is presented that illustrates the practical implementation of this concept. This digital payload architecture demonstrates that with the advent of high performance CMOS digital processing, the on-board implementation of complex DSP techniques - in particular Digital Beamforming - has become possible, being most attractive for Mobile Satellite Communications.

Munoz-Garcia, Samuel G.↗
NASA NTRS1998

Evaluation and optimization of lidar temperature analysis algorithms using simulated data

The middle atmosphere (20 to 90 km altitude) ha received increasing interest from the scientific community during the last decades, especially since such problems as polar ozone depletion and climatic change have become so important. Temperature profiles have been obtained in this region using a variety of satellite-, rocket-, and balloon-borne instruments as well as some ground-based systems. One of the more promising of these instruments, especially for long-term high resolution measurements, is the lidar. Measurements of laser radiation Rayleigh backscattered, or Raman scattered, by atmospheric air molecules can be used to determine the relative air density profile and subsequently the temperature profile if it is assumed that the atmosphere is in hydrostatic equilibrium and follows the ideal gas law. The high vertical and spatial resolution make the lidar a well adapted instrument for the study of many middle atmospheric processes and phenomena as well as for the evaluation and validation of temperature measurements from satellites, such as the Upper Atmosphere Research Satellite (UARS). In the Network for Detection of Stratospheric Change (NDSC) lidar is the core instrument for measuring middle atmosphere temperature profiles. Using the best lidar analysis algorithm possible is therefore of crucial importance. In this work, the JPL and CNRS/SA lidar analysis software were evaluated. The results of this evaluation allowed the programs to be corrected and optimized and new production software versions were produced. First, a brief description of the lidar technique and the method used to simulate lidar raw-data profiles from a given temperature profile is presented. Evaluation and optimization of the JPL and CNRS/SA algorithms are then discussed.

Leblanc, Thierry↗
DOE OSTI2025

Comments on “Failure analysis of corroded hydrogen-blended natural gas pipelines based on finite element analysis and genetic algorithm-back propagation neural network” [262 (2025) 111174]

This is a brief commentary paper to highlight and discuss the determination of hydrogen concentration in pipeline steel, effect of hydrogen embrittlement (HE) on the mechanical properties of the material, burst strength of corroded pipelines using finite element analysis (FEA) simulations, and curve-fit models for assessing remaining strength of X80 corroded pipelines for transporting hydrogen blended natural gas. Recently, Xie et al. [1] proposed a methodology to quantify the impact of HE on material properties and numerically determined burst pressure of X80 corroded pipelines. However, their HE quantification overestimated the degradation of tensile strength for hydrogen blending ratios beyond the original data range, and their FEA results of burst pressure are nonconservative. This work thus recharacterized the hydrogen concentration in the steel pipeline and the effect of HE on tensile strength, and then redetermined burst pressures for a set of typical corrosion defect cases considered by Xie et al. [1] based on an experimentally validated FEA modelling method. With the new FEA results, two empirical corrosion models were proposed for X80 corroded pipelines for hydrogen service. At zero hydrogen blending ratio, the novel empirical models predict burst pressures to be consistent with the industry-accepted corrosion models. Furthermore, both the numerical simulation method and the novel corrosion models are significant contributions to the pipeline industry and the hydrogen community. Application of these results will enhance the safety, reliability, and integrity of natural gas pipelines when used to transport hydrogen.

Burst pressure prediction↗
NASA NTRS2012

Evaluation of NASA SPoRT's Pseudo-Geostationary Lightning Mapper Products in the 2011 Spring Program

NASA's Short-term Prediction Research and Transition (SPoRT) program is a contributing partner with the GOES-R Proving Ground (PG) preparing forecasters to understand and utilize the unique products that will be available in the GOES-R era. This presentation emphasizes SPoRT s actions to prepare the end user community for the Geostationary Lightning Mapper (GLM). This preparation is a collaborative effort with SPoRT's National Weather Service partners, the National Severe Storms Laboratory (NSSL), and the Hazardous Weather Testbed s Spring Program. SPoRT continues to use its effective paradigm of matching capabilities to forecast problems through collaborations with our end users and working with the developers at NSSL to create effective evaluations and visualizations. Furthermore, SPoRT continues to develop software plug-ins so that these products will be available to forecasters in their own decision support system, AWIPS and eventually AWIPS II. In 2009, the SPoRT program developed the original pseudo geostationary lightning mapper (PGLM) flash extent product to demonstrate what forecasters may see with GLM. The PGLM replaced the previous GLM product and serves as a stepping-stone until the AWG s official GLM proxy is ready. The PGLM algorithm is simple and can be applied to any ground-based total lightning network. For 2011, the PGLM used observations from four ground-based networks (North Alabama, Kennedy Space Center, Oklahoma, and Washington D.C.). While the PGLM is not a true proxy product, it is intended as a tool to train forecasters about total lightning as well as foster discussions on product visualizations and incorporating GLM-resolution data into forecast operations. The PGLM has been used in 2010 and 2011 and is likely to remain the primary lightning training tool for the GOES-R program for the near future. This presentation will emphasize the feedback received during the 2011 Spring Program. This will discuss several topics. Based on feedback from the 2010 Spring Program, SPoRT created two variant PGLM products, which NSSL produced locally and provided in real-time within AWIPS for 2011. The first is the flash initiation density (FID) product, which creates a gridded display showing the number of flashes that originated in each 8 8 km grid box. The second product is the maximum flash density (MFD). This shows the highest PGLM value for each grid point over a specific period of time, ranging from 30 to 120 minutes. In addition to the evaluation of these two new products, the evaluation of the PGLM itself will be covered. The presentation will conclude with forecaster feedback for additional improvements requested for future evaluations, such as within the 2012 Spring Program.

Stano, Geoffrey T.↗
NASA NTRS2012

An Analysis of Operational Total Lightning Data During Long-Track Tornadoes

The 27 April 2011 tornado outbreak brought three distinct waves of tornadic thunderstorms to portions of Mississippi, Alabama, Tennessee, and Georgia, striking the Tennessee Valley of north Alabama and southern Tennessee particularly hard. A total of 42 tornado paths were surveyed across the fourteen county area covered by the National Weather Service (NWS) forecast office in Huntsville, Alabama. Ten of these tornadoes were on the ground for at least 20 miles, two had total path lengths over 130 miles, and six tornadoes were classified as violent (EF-4 or EF-5 on the Enhanced Fujita Scale). Many of these tornadoes occurred within the domain of the North Alabama Lightning Mapping Array (NALMA), a ground-based total lightning detection network owned and operated by the NASA Marshall Space Flight Center. Since 2003, the NASA Short-term Prediction Research and Transition Center has supplied data from NALMA in real time to NWS forecast offices in Huntsville, Knoxville/Tri-Cities, Birmingham, and Nashville. Previous research has documented the utility of total lightning information in predicting tornadogenesis, particularly when combined with other remote sensing tools. Basic warning decision-making during events such as 27 April is not the most difficult part of the process; instead, the focus of warning meteorologists shifts to looking for changes in intensity or possible particularly dangerous situations, since doppler radar velocity data often cannot distinguish between weak and strong tornadoes. To that end, this research attempts to determine if any correlation exists between flash densities of the longest-tracked tornadoes over time, and the surveyed wind speeds of the tornadoes. The long-track EF-5 tornado which struck the Hackleburg, Phil Campbell, and Tanner communities in north Alabama was the primary focus of this research due to its intensity and extended life cycle. However, not all tornadoes were available for total lightning analysis due to widespread power outages which negatively affected the detection efficiency and operation of the NALMA. Therefore, additional storms from 2008-2010 with tracks of at least 20 miles were analyzed for comparison purposes.

Carcione, Brian C.↗