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NASA NTRS2015

NASA Software Cost Estimation Model: An Analogy Based Estimation Model

The cost estimation of software development activities is increasingly critical for large scale integrated projects such as those at DOD and NASA especially as the software systems become larger and more complex. As an example MSL (Mars Scientific Laboratory) developed at the Jet Propulsion Laboratory launched with over 2 million lines of code making it the largest robotic spacecraft ever flown (Based on the size of the software). Software development activities are also notorious for their cost growth, with NASA flight software averaging over 50% cost growth. All across the agency, estimators and analysts are increasingly being tasked to develop reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods there is very little focus on the use of models based on analogy and clustering algorithms. In this paper we summarize our findings on effort/cost model estimation and model development based on ten years of software effort estimation research using data mining and machine learning methods to develop estimation models based on analogy and clustering. The NASA Software Cost Model performance is evaluated by comparing it to COCOMO II, linear regression, and K- nearest neighbor prediction model performance on the same data set.

Hihn, Jairus↗

NASA NTRSDate not supplied

Towards Automated Analytics of Research Publications

For readers of scientific publications it remains a big challenge to unambiguously relate the published research with the data used. To a substantial degree it is attributed to authors, journals, editors, and reviewers not prioritizing correct data citation, which impacts traceability, repeatability, and giving credits to published authors and their funding sources. Furthermore, uniform classification of the content of the published research is hampered by journals using journal specific topics and letting authors to assign free text keywords to their papers. We demonstrate automated analytics methods for extracting and relating datasets used and the research application areas by processing 1,300 research papers that referenced the NASA Giovanni service (but probably not the datasets in particular) as supporting their publication process. This presentation was given during the 2022 ESIP January meeting held virtually in January 2022.

Irina Gerasimov↗

NASA NTRS2022

Space Communications Responsive to Events Across Missions (SCREAM): An Investigation of Network Solutions for Transient Science Space Systems

Space Communications Responsive to Events Across Missions (SCREAM): An Investigation of Network Solutions for Transient Science Space Systems The National Academies have prioritized the pursuit of new scientific discoveries using diverse and temporally coordinated measurements from multiple ground and space-based observatories. Networked communications can enable such measurements by connecting individual observatories and allowing them to operate as a cohesive and purposefully designed system. Timely data flows across terrestrial and space communications networks are required to observe transient scientific events and processes. Currently, communications to space-based observatories experience large latencies due to manual service reservation and scheduling procedures, intermittent signal coverage, and network capacity constraints. If space communications network latencies could be reduced, new discoveries about dynamic scientific processes could be realized. However, science mission and network planners lack a systematic framework for defining, quantifying and evaluating timely space data flow implementation options for transient scientific observation scenarios involving multiple ground and space-based observatories. This dissertation presents a model-based systems engineering approach to investigate and develop network solutions to meet the needs of transient science space systems. First, a systematic investigation of the current transient science operations of the National Aeronautics and Space Administration’s (NASA) Tracking and Data Relay Satellite (TDRS) space data network and the Neil Gehrels Swift Observatory resulted in a formal architectural model for transient science space systems. Two methods individual missions may use to achieve timely network services were defined, quantitatively modeled, and experimentally compared. Next, the architectural model was extended to describe two alternative ways to achieve timely and autonomous space data flows to multiple space-based observatories within the context of a purposefully designed transient science observation scenario. A quantitative multipoint space data flow modeling method based in queueing theory was defined. General system suitability metrics for timeliness, throughput, and capacity were specified to support the evaluation of alternative network data flow implementations. A hypothetical design study was performed to demonstrate the multipoint data flow modeling method and to evaluate alternative data flow implementations using TDRS. The merits of a proposed future TDRS broadcast service to implement multipoint data flows were quantified and compared to expected outcomes using the as-built TDRS network. Then, the architectural model was extended to incorporate commercial network service providers. Quantitative models for Globalstar and Iridium short messaging data services were developed based on publicly available sources. Financial cost was added to the set of system suitability metrics. The hypothetical design study was extended to compare the relative suitability of the as-built TDRS network with the commercial Globalstar and Iridium networks. Finally, results from this research are being applied by NASA missions and network planners. In 2020, Swift implemented the first automated command pipeline, increasing its expected gravitational wave follow-up detection rate by greater than 400%. Current NASA technology initiatives informed by this research will enable future space-based observatories to become interoperable sensing devices connected by a diverse ecosystem of network service providers.

Christopher J. Roberts↗

NASA NTRSDate not supplied

Performance Analysis of Magnetohydrodynamic Drag Modulation for Actively Controlled Aerocapture at Neptune

While the Ice Giants are a top priority for flagship missions in the NASA’s near-term future, current technologies limit the scientific payload and mission timeline for future Uranian and Neptunian missions due to the need for fuel for orbit insertion maneuvers. Thus, to maximize the scientific potential of future missions, atmospheric aerocapture has been heavily researched. While atmospheric aerocapture simulations have proven enabling for capturing around Neptune, its deep atmospheric pass requires an aeroshell with robust thermal protection systems (TPS). Magnetohydrodynamically-controlled aerocapture serves as a potential solution to the limitations of both fully propulsive orbit insertion and aerodynamically controlled aerocapture. Through NASA Langley’s high-fidelity flight dynamics simulation, the Program to Optimize Simulated Trajectories II, both the aerodynamic-only and magnetohydrodynamic aerocapture methods were simulated and compared for identical missions to Neptune. After applying an optimized numerical predictor-corrector guidance algorithm for both methods, the results showed that magnetohydrodynamics has not only the control authority to successfully capture around Neptune, but also the unique advantage of a shallower atmospheric pass, decreasing the maximum heat load and the required TPS mass.

Danny N. Nguyen↗

DOE OSTI2021

Standards development for modules in high temperature micro-environments

Photovoltaic (PV) module qualification standards, IEC 61215 and IEC 61730, were designed to apply to “general open-air climates” and IEC 61730 specifically indicated applicability of ambient air temperature of 40°C. Additionally, these standards provided allowances for so-called “open rack mounted PV modules” without a clear definition of “open-rack.” These implied restrictions and allowances meant that hotter climates or thermally restrictive installation methods may not be covered by these often customer-mandated certification standards. This is particularly salient for the significant growth regions of the Middle East and India that would be expected to operate at significantly higher temperatures. The applicability of these documents raised issues over the definition of “open rack” and the fact that the geographic location is just as important as the mounting configuration in assessing the impact of the micro-environment of a PV module. This work summarizes the scientific background for IEC Technical Specification 63126:2020 ED1, titled “Guidelines for qualifying PV modules components and materials for operation at high temperatures.” This standard was recently published by the IEC and is the first step in a systematic effort to rework these standards to address the question of temperature more directly. Instead of specifying a mounting condition, we specify different suites of tests suitable for a system (PV module, mounting style, and location) defined by the 98th percentile cell temperature. With a defined temperature regime to work from, this allowed us to use existing literature research combined with additional modeling work to determine, which tests would need to be modified. This resulted in suggested changes to material thermal indices, thermal cycling temperatures, hot spot testing, ultraviolet testing, and bypass diode testing among other tests and characteristics described in this study.

14 SOLAR ENERGY↗

DOE OSTI2024

Deep Generative Models in Energy System Applications: Review, Challenges, and Future Directions

In recent years, with the advent of mature machine learning products like ChatGPT, Stable Diffusion, and Sora, the world has witnessed tremendous changes driven by the rapid development of generative artificial intelligence (GAI). Beyond applications in text, speech, image, and video creation, deep generative models (DGMs) underpinning these cutting-edge technologies have also been employed by domain researchers to address scientific and engineering challenges. This paper aims to fill a gap in the research community by providing a systematic review of how DGMs have been utilized in energy system applications. After introducing four most popular DGMs, we review and categorize 196 research articles into five focus areas: data generation, forecasting, situational awareness, modeling, and optimal decision-making. Through this classification, we uncover trends in how DGMs are employed for each type of problem, highlighting GAI techniques that contribute to breakthroughs over traditional methods. We discuss limitations in existing literature, engineering challenges, and propose future directions, all tailored to the unique nature of problems in energy system engineering. Our goal is to offer insights for energy system domain researchers, providing a comprehensive view of existing studies and potential future opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Applications of physics informed neural operators

Abstract We present a critical analysis of physics-informed neural operators (PINOs) to solve partial differential equations (PDEs) that are ubiquitous in the study and modeling of physics phenomena using carefully curated datasets. Further, we provide a benchmarking suite which can be used to evaluate PINOs in solving such problems. We first demonstrate that our methods reproduce the accuracy and performance of other neural operators published elsewhere in the literature to learn the 1D wave equation and the 1D Burgers equation. Thereafter, we apply our PINOs to learn new types of equations, including the 2D Burgers equation in the scalar, inviscid and vector types. Finally, we show that our approach is also applicable to learn the physics of the 2D linear and nonlinear shallow water equations, which involve three coupled PDEs. We release our artificial intelligence surrogates and scientific software to produce initial data and boundary conditions to study a broad range of physically motivated scenarios. We provide the source code , an interactive website to visualize the predictions of our PINOs, and a tutorial for their use at the Data and Learning Hub for Science .

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

X-ray microscopy enables multiscale high-resolution 3D imaging of plant cells, tissues, and organs

Capturing complete internal anatomies of plant organs and tissues within their relevant morphological context remains a key challenge in plant science. While plant growth and development are inherently multiscale, conventional light, fluorescence, and electron microscopy platforms are typically limited to imaging of plant microstructure from small flat samples that lack a direct spatial context to, and represent only a small portion of, the relevant plant macrostructures. We demonstrate technical advances with a lab-based X-ray microscope (XRM) that bridge the imaging gap by providing multiscale high-resolution three-dimensional (3D) volumes of intact plant samples from the cell to the whole plant level. Serial imaging of a single sample is shown to provide sub-micron 3D volumes co-registered with lower magnification scans for explicit contextual reference. High-quality 3D volume data from our enhanced methods facilitate sophisticated and effective computational segmentation. Advances in sample preparation make multimodal correlative imaging workflows possible, where a single resin-embedded plant sample is scanned via XRM to generate a 3D cell-level map, and then used to identify and zoom in on sub-cellular regions of interest for high-resolution scanning electron microscopy. In total, we present the methodologies for use of XRM in the multiscale and multimodal analysis of 3D plant features using numerous economically and scientifically important plant systems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Deep learning-based spatio-temporal fusion for high-fidelity ultra-high-speed X-ray radiography

Full-field ultra-high-speed (UHS) X-ray imaging experiments have been well established to characterize various processes and phenomena. However, the potential of UHS experiments through the joint acquisition of X-ray videos with distinct configurations has not been fully exploited. In this paper, we investigate the use of a deep learning-based spatio-temporal fusion (STF) framework to fuse two complementary sequences of X-ray images and reconstruct the target image sequence with high spatial resolution, high frame rate and high fidelity. We applied a transfer learning strategy to train the model and compared the peak signal-to-noise ratio (PSNR), average absolute difference (AAD) and structural similarity (SSIM) of the proposed framework on two independent X-ray data sets with those obtained from a baseline deep learning model, a Bayesian fusion framework and the bicubic interpolation method. The proposed framework outperformed the other methods with various configurations of the input frame separations and image noise levels. With three subsequent images from the low-resolution (LR) sequence of a four times lower spatial resolution and another two images from the high-resolution (HR) sequence of a 20 times lower frame rate, the proposed approach achieved average PSNRs of 37.57 dB and 35.15 dB, respectively. When coupled with the appropriate combination of high-speed cameras, the proposed approach will enhance the performance and therefore the scientific value of UHS X-ray imaging experiments.

deep learning↗

DOE OSTI2022

Dynamic Differential Image Circle Diameter Measurement Precision Assessment: Application to Burning Droplets

Dynamic measurement precision assessment has been achieved for a differential circle measurement application. Differential circle diameter measurement, in image analysis, typically requires fitting a circle model that optimizes for image distortions, defects or occlusions. The differential task occurs when precise measurements of diameter change are required given object size variation with time. An automated system was designed to provide diameter measurements and associated measurement precision of images of a fuel droplet undergoing combustion in zero gravity for the FLEX-2 dataset. An image gradient-based, least-squares boundary point fitting method to a circle or ellipse model is used for diameter measurement. The presence of soot aggregates poses significant challenges for diameter measurements when it occludes part of the droplet boundary. The precision of the diameter measurements depends upon the image quality. Using synthetic image simulations that model the soot behavior, we developed a model based on image quality measures that assesses the measurement precision for each individual diameter measurement. Thus, diameter measurements with precision assessments were made available for follow-up scientific analysis. As a result, the algorithm's success rate for measurable runs was 98%. In cases of limited occlusion, a measurement precision of ±0.2 pixels for the FLEX-2 dataset was achieved.

42 ENGINEERING↗

DOE OSTI2020

Accelerator physics at NSLS-II: research accomplishments in 2020

NSLS-II accelerator physicists provide scientific support for user operations, as well as for improvements and developments of the accelerator systems. This work includes optimization of the NSLS-II performance with high beam current and low vertical emittance, improvement of the beam stability, development of new software tools for operations and beam studies. The accelerator physicists productively worked on a number of research activities such as the conceptual design of NSLS-II accelerator upgrade; design and optimization of advanced low-emittance lattices; development of novel methods to study nonlinear beam dynamics; ultrafast electron diffraction and microscopy. The physicists also contributed to the BNL electron-ion collider project, to the APS and ALS upgrade projects. Research accomplishments achieved in 2020, are summarized in this report.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

A Block-Structured Adaptive Mesh Framework to Solve Radiation Transfer Equation in Irregular Embedded Geometries

Radiation transport arises in various scientific, industrial, and medical fields, and understanding its effect in applications is needed to make accurate predictions, safety assessments and performance optimizations. Solving the Radiation Transport Equation (RTE) is challenging due to its integro-differential nature, which involves both differential and integral terms. The differential term describes the change in radiation intensity due to absorption and emission, while the integral term accounts for scattering. The accurate modeling of radiation is further complicated in many applications due to the complex, irregular geometries. Various methods exist for solving the RTE, including the zonal, Monte Carlo, spherical harmonics, discrete ordinates, and finite volume methods. Traditional mesh-based approaches, which rely on structured or unstructured meshes, struggle with irregular geometries due to: a) the difficulty of conforming structured grids to irregular domains, b) challenges in enforcing boundary conditions correctly, and c) the additional computational cost of unstructured mesh methods. This work presents a second-order accurate method for solving the RTE in irregular geometries. The radiation intensity is discretized using the finite-volume method in both spatial and angular directions on regular Cartesian grid blocks. Leveraging the block-structured adaptive mesh refinement (AMR) framework provided by AMReX, our method refines the grid locally to reduce spatial discretization error, ensuring a converged numerical solution while minimizing computational costs elsewhere. A two-stage deferred correction approach is employed: First, a first-order discretization on grid blocks is solved using an algebraic multigrid method in HYPRE. Second, a correction term is applied explicitly to achieve second-order accuracy. The correction term is calculated by approximating the radiation flux on cell faces using a Total Variation Diminishing (TVD) scheme. This approach ensures quick convergence of the multigrid method while preserving higher-order accuracy of the numerical solution. Irregular geometries are resolved as embedded boundaries (EB), resulting in both cut cells and regular cells. In cut cells, we modify the fluxes using face fractions and incorporate additional contributions from EB boundary conditions. To ensure higher-order convergence near the EB interface, the correction term is modified by interpolating the radiation intensity to fictitious ghost points. The implementation takes advantage of modern supercomputers by leveraging AMReX’sMPI/X parallelization strategy where X can be MPI or a GPU accelerator including CUDA, HIP and DPC++. We validate our solver using classical test cases, both with and without EB, demonstrating accuracy and efficiency. Additionally, we analyze the impact of adaptive mesh refinement on solution accuracy and computational cost, highlighting the advantages of our approach for high-resolution radiation transport simulations.

computational fluid dynamics (CFD)↗

NASA NTRS1976

Experiments on the properties of superfluid helium in zero gravity

The paper describes a research program designed to study the behavior of superfluid liquid helium in low and zero gravity in order to determine the properties which are critically important to its use as a stored cryogen for cooling scientific instruments aboard spacecraft for periods up to several months. The experiment program consists of a series of flights of an experiment package on a free-fall trajectory both on an aircraft and on a rocket. The objectives are to study thickness of thin films of helium as a function of acceleration, heat transfer in thin films, heat transfer across copper-liquid helium interfaces, fluid dynamics of bulk helium in high and low accelerations and under various conditions of rotations, alternate methods of separation of liquid and vapor phases and of efficient venting of the vapor, and undesirable thermomechanical oscillations in the vent pipes. Preliminary results from aircraft tests are discussed.

Mason, P.↗

NASA NTRS1987

Maintaining an expert system for the Hubble Space Telescope ground support

The transformation portion of the Hubble Space Telescope (HST) Proposal Entry Processor System converts astronomer-oriented description of a scientific observing program into a detailed description of the parameters needed for planning and scheduling. The transformation system is one of a very few rulebased expert systems that has ever entered an operational phase. The day to day operations of the system and its rulebase are no longer the responsibility of the original developer. As a result, software engineering properties of the rulebased approach become more important. Maintenance issues associated with the coupling of rules within a rulebased system are discussed and a method is offered for partitioning a rulebase so that the amount of knowledge needed to modify the rulebase is minimized. This method is also used to develop a measure of the coupling strength of the rulebase.

Lindenmayer, Kelly↗

NASA NTRS2005

Robotic Technologies for Surveying Habitats and Seeking Evidence of Life: Results from the 2004 Field Experiments of the "Life in the Atacama" Project

The Chilean Atacama Desert is the most arid region on Earth and in several ways analogous to Mars. Evidence suggests that the interior of the Atacama is lifeless, yet where the desert meets the Pacific coastal range dessication-tolerant microorganisms are known to exist. The gradient of biodiversity and habitats in the Atacama's subregions remain unexplored and are the focus of the Life in the Atacama project. Our field investigation attempts to bring further scientific understanding of the Atacama as a habitat for life through the creation of robotic astrobiology. This involves capabilities for autonomously traversing hundreds of kilometers while deploying sensors to survey the varying geologic and biologic properties of the environment, Fig. 1. Our goal is to make genuine discoveries about the limits of life on Earth and to generate knowledge about life in extreme environments that can be applied to future planetary missions. Through these experiments we also hope to develop and practice the methods by which a rover might best be employed to survey desert terrain in search of the habitats in which life can survive, or may have in the past.

Wettergreen, D.↗

NASA NTRS2016

Cassini Maneuver Performance Assessment and Execution-Error Modeling Through 2015

In its twelfth year touring Saturn, the Cassini spacecraft continues to gather valuable scientific data about the planet and its moons. Cassini has executed a total of 331 propulsive maneuvers through January 23, 2016. With more than 30 maneuvers planned through July 2017 before the mission ends in September 2017, a dwindling propellant supply has become a chief concern. This manuscript will report on the analysis of Cassini maneuvers performed through December 30, 2015 and recommend execution-error models for the remainder of the mission. Maneuver performance assessment techniques and execution-error model development methods will also be outlined.

Wagner, Sean V.↗

NASA NTRS2016

Cassini Maneuver Performance Assessment and Execution-Error Modeling Through 2015

Wagner, Sean V.↗

DOE OSTI2026

Scientific Discovery with Physics-Informed System Identification (Abbreviated Report)

My fellowship research focused on making physics-based simulations faster and more useful through machine learning. Many problems in science and engineering are governed by partial differential equations, but high-fidelity simulations are often too expensive to run repeatedly. I worked on improving Latent Space Dynamics Identification (LaSDI), a reduced-order modeling framework that compresses large simulation data sets into a smaller representation and then learns how that representation evolves over time. The motivation was to develop reduced models that remain accurate for more challenging systems, especially when predictions must remain reliable over long time intervals or when the underlying dynamics are more complicated than standard methods can easily handle. I also contributed to related work on Quandary, a high-performance software effort for simulation and control of open quantum systems, before focusing primarily on Latent Space Dynamics Identification methods. The main outcomes of the fellowship were two new algorithms (both of which were published), Rollout-LaSDI and Higher-Order LaSDI, together with supporting work on multi-stage Latent Space Dynamics Identification. Rollout-LaSDI improved long-term prediction by training the model to stay accurate over extended time horizons, and Higher-Order LaSDI broadened the method so it could model systems with higher-order time dynamics. My contributions to multistage Latent Space Dynamics Identification also helped show that its later training stages could be simplified without losing effectiveness, and that this behavior held across different model architectures and training strategies. Taken together, these advances improved the accuracy, flexibility, and practical value of reduced-order modeling tools for computational science.

97 MATHEMATICS AND COMPUTING↗