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At least 1,747 records · Page 97

North Pacific Mesoscale Coupled Air-Ocean Simulations Compared with Observations

Executive summary The main objective of the study was to investigate atmospheric and ocean interaction processes in the western Pacific and, in particular, effects of significant ocean heat loss in the Kuroshio and Kuroshio Extension regions on the lower and upper atmosphere. It is yet to be determined how significant are these processes are on climate scales. The understanding of these processes led us also to development of the methodology of coupling the Weather and Research Forecasting model with the Parallel Ocean Program model for western Pacific regional weather and climate simulations. We tested NCAR-developed research software Coupler 7 for coupling of the WRF and POP models and assessed its usability for regional-scale applications. We completed test simulations using the Coupler 7 framework, but implemented a standard WRF model code with options for both one- and two-way mode coupling. This type of coupling will allow us to seamlessly incorporate new WRF updates and versions in the future. We also performed a long-term WRF simulation (15 years) covering the entire North Pacific as well as high-resolution simulations of a case study which included extreme ocean heat losses in the Kuroshio and Kuroshio Extension regions. Since the extreme ocean heat loss occurs during winter cold air outbreaks (CAO), we simulated and analyzed a case study of a severe CAO event in January 2000 in detail. We found that the ocean heat loss induced by CAOs is amplified by additional advection from mesocyclones forming on the southern part of the Japan Sea. Large scale synoptic patterns with anomalously strong anticyclone over Siberia and Mongolia, deep Aleutian Low, and the Pacific subtropical ridge are a crucial setup for the CAO. It was found that the onset of the CAO is related to the breaking of atmospheric Rossby waves and vertical transport of vorticity that facilitates meridional advection. The study also indicates that intrinsic parameterization of the surface fluxes within the WRF model needs more evaluation and analysis.

54 ENVIRONMENTAL SCIENCES↗

Straight Line Geometric Path Lengths – Examples and Distributions

The straight line geometric path distribution of different shapes is a fundamental parameter of any a detector sensitive and in the presence of high energy charged particles such as galactic cosmic rays (GCRs). Knowledge of the straight line path distribution can yield first estimates of the expected energy distribution due to minimum ionizing particles. This predicted shape provides a valuable interpretation tool of spectra of particles that are unlikely to stop in a detector and may present a background or desired signal. These quantities have been calculated many times before including analytically, Coleman (1973), and even in Geant4 software, (Agostinelli, Allison et al. 2003, Santin, Ivanchenko et al. 2005). For this work we utilize the Rapid Adaptable Multi-threaded Particle and Radiation Transport (RAMPART) simulation framework and collect some common shapes all with the same volume to serve as a reference of path lengths and instructions manual for computing other shapes as desired.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NMSBA Sustainable Engineering (Final Report)

This report summarizes the guidance provided to Sustainable Engineering to help them learn about equation-oriented optimization and the Sandia-developed software packages Pyomo and IDAESPSE. This was a short 10-week project (October 2021 – December 2021) and the goal was to help the company learn about the IDAES framework and how it could be used for their future projects. The company submitted an SBIR proposal related to developing a green ammonia process model with IDAES and if that proposal is successful this NMSBA project could lead to future collaboration opportunities.

42 ENGINEERING↗

Development of a prototype spatial information processing system for hydrologic research

Significant advances have been made in the last decade in the areas of Geographic Information Systems (GIS) and spatial analysis technology, both in hardware and software. Science user requirements are so problem specific that currently no single system can satisfy all of the needs. The work presented here forms part of a conceptual framework for an all-encompassing science-user workstation system. While definition and development of the system as a whole will take several years, it is intended that small scale projects such as the current work will address some of the more short term needs. Such projects can provide a quick mechanism to integrate tools into the workstation environment forming a larger, more complete hydrologic analysis platform. Described here are two components that are very important to the practical use of remote sensing and digital map data in hydrology. Described here is a graph-theoretic technique to rasterize elevation contour maps. Also described is a system to manipulate synthetic aperture radar (SAR) data files and extract soil moisture data.

Sircar, Jayanta K.↗

Automatic Parameter Tuning for the Morpheus Vehicle Using Particle Swarm Optimization

A high fidelity simulation using a PC based Trick framework has been developed for Johnson Space Center's Morpheus test bed flight vehicle. There is an iterative development loop of refining and testing the hardware, refining the software, comparing the software simulation to hardware performance and adjusting either or both the hardware and the simulation to extract the best performance from the hardware as well as the most realistic representation of the hardware from the software. A Particle Swarm Optimization (PSO) based technique has been developed that increases speed and accuracy of the iterative development cycle. Parameters in software can be automatically tuned to make the simulation match real world subsystem data from test flights. Special considerations for scale, linearity, discontinuities, can be all but ignored with this technique, allowing fast turnaround both for simulation tune up to match hardware changes as well as during the test and validation phase to help identify hardware issues. Software models with insufficient control authority to match hardware test data can be immediately identified and using this technique requires very little to no specialized knowledge of optimization, freeing model developers to concentrate on spacecraft engineering. Integration of the PSO into the Morpheus development cycle will be discussed as well as a case study highlighting the tool's effectiveness.

Birge, B.↗

Exploration Medical System Demonstration

BACKGROUND: Exploration class missions will present significant new challenges and hazards to the health of the astronauts. Regardless of the intended destination, beyond low Earth orbit a greater degree of crew autonomy will be required to diagnose medical conditions, develop treatment plans, and implement procedures due to limited communications with ground-based personnel. SCOPE: The Exploration Medical System Demonstration (EMSD) project will act as a test bed on the International Space Station (ISS) to demonstrate to crew and ground personnel that an end-to-end medical system can assist clinician and non-clinician crew members in optimizing medical care delivery and data management during an exploration mission. Challenges facing exploration mission medical care include limited resources, inability to evacuate to Earth during many mission phases, and potential rendering of medical care by non-clinicians. This system demonstrates the integration of medical devices and informatics tools for managing evidence and decision making and can be designed to assist crewmembers in nominal, non-emergent situations and in emergent situations when they may be suffering from performance decrements due to environmental, physiological or other factors. PROJECT OBJECTIVES: The objectives of the EMSD project are to: a. Reduce or eliminate the time required of an on-orbit crew and ground personnel to access, transfer, and manipulate medical data. b. Demonstrate that the on-orbit crew has the ability to access medical data/information via an intuitive and crew-friendly solution to aid in the treatment of a medical condition. c. Develop a common data management framework that can be ubiquitously used to automate repetitive data collection, management, and communications tasks for all activities pertaining to crew health and life sciences. d. Ensure crew access to medical data during periods of restricted ground communication. e. Develop a common data management framework that allows for scalability, extensibility, and interoperability of data sources and data users. f. Lower total cost of ownership for development and sustainment of peripheral hardware and software that use EMSD for data management. g. Provide a better standard of healthcare for crew members through reductions in the time required by crew and ground personnel to provide medical treatment and the number of crew errors experienced during treatment.

Rubin, D. A.↗

pFUnit 3.0 Tutorial Advanced

This tutorial will introduce Fortran developers to unit-testing and test-driven development (TDD) using pFUnit. As with other unit-testing frameworks, pFUnit, simplifies the process of writing, collecting, and executing tests while providing clear diagnostic messages for failing tests. pFUnit specifically targets the development of scientific-technical software written in Fortran and includes customized features such as: assertions for multi-dimensional arrays, distributed (MPI) and thread-based (OpenMP) parallellism, and flexible parameterized tests.These sessions will include numerous examples and hands-on exercises that gradually build in complexity. Attendees are expected to have working knowledge of F90, but familiarity with object-oriented syntax in F2003 and MPI will be of benefit for the more advanced examples. By the end of the tutorial the audience should feel comfortable in applying pFUnit within their own development environment.

Test Driven using pFUnit↗

Simplifying Requirements Formalization for Resource-Constrained Mission-Critical Software

Developing critical software requires adherence to rigorous software development practices, such as formal requirement specification and verification. Despite their importance, such practices are often considered as complex and challenging tasks that require a strong formal methods background. In this paper, we present our work on simplifying the formal requirements specification experience for resource-constrained mission critical software through the use of structured natural language. To this end, we connect NASA’s FRET, a formal requirement elicitation and authoring tool with the Shelley model checking framework for MicroPython code. We report our experience on using these tools to specify requirements and analyze code from the NASA Ames PHALANX exploration concept.

PHALANX exploration concept↗

Parametric-Based Heat Rejection Trade Study for Lunar and Martian Surface Operations

Establishing and maintaining a sustained presence on the lunar and/or Martian surfaces will require a diverse portfolio of surface elements (e.g., habitation, mobility, power generation, etc.). Many of these systems generate excess heat that must be rejected across a wide range of magnitudes, temperatures, and duty cycles and under variable environmental conditions. To identify the most promising heat rejection approaches for this diverse portfolio, a heat rejection trade study was conducted to evaluate the performance of different technology approaches across a spectrum of surface environments and heat-load requirements. The trade study consisted of three stages: (1) development of a parametric-based modeling framework, (2) creation of a database of heat rejection technologies, surface elements, and environmental conditions for the Moon and Mars, and (3) execution of a quantitative analysis of various heat rejection technologies across different operating conditions and surface elements. The modeling framework is developed in Python and Excel to prioritize small model size and hence low computational cost to enable large parametric sweeps while avoiding the reliance on proprietary software. Individual heat rejection processes are represented as simple Excel models, and a centralized Python script interfaces with the models to coordinate the parametric study. These simple sizing models were developed to take heat load requirements and environmental parameters as inputs and compute mass, power, and volume as outputs. Rather than assess each heat rejection technology separately for each surface element, a unified parametric space was developed to evaluate all technologies across all elements. This parametric space includes factors related to heat load (e.g., magnitude or temperature) and environment (e.g., surface temperature, sky temperature, solar flux). This effort generated a database containing information on over 60 heat rejection technologies and 30 surface elements. For each surface element, the expected heat rejection requirements were documented and analyzed to determine the most common needs shared across all elements. Environmental conditions at various lunar and Martian latitudes were also established for worst-case hot and worst-case cold scenarios. High-fidelity heat rejection models are currently under development. Preliminary trades between heat rejection technologies including radiators, venting technologies, convective coolers, and more have been conducted to identify promising options. This presentation will summarize the preliminary trade results and provide an overview and discussion of the expected heat loads and thermal environments for sustained surface operations on the Moon and Mars.

Heat Rejection↗

Streaming Analytics and Data Engineering

SADE is a software package for rapidly assembling analytic pipelines to manipulate data. The packages consists of the engine that manages the data and coordinates the movement of data between the tasks performing a function, a set of core libraries consisting of plugins that perform common tasks, and a framework to extend the system supporting the development of new plugins. Currently through configuration files, a pipeline can be defined that maps the routing of data through a series of plugins. Pipelines can be run in a batch mode or can process streaming data; they can be executed from the command line or run through a Windows background service. There currently exists over a hundred plugins, over fifty pipeline configurations, and the software is now being used by about a half-dozen projects.

Source record↗

How does the connectivity of open-framework conglomerates within multi-scale hierarchical fluvial architecture affect oil-sweep efficiency in waterflooding?

Understanding multi-phase fluid flow and transport processes within aquifers, candidate reservoirs for CO 2 sequestration, and petroleum reservoirs requires understanding a diverse set of geologic properties of the aquifer or reservoir, over a wide range of spatial and temporal scales. We focus on multiphase flow dynamics with wetting (e.g., water) and non-wetting (e.g., gas or oil) fluids, with one invading another. This problem is of general interest in a number of fields and is illustrated here by considering the sweep efficiency of oil during a waterflood. Using a relatively fine-resolution grid throughout a relatively large domain in these simulations and probing the results with advanced scientific visualization tools (Reservoir Visualization Analysis [RVA]/ ParaView software) promote a better understanding of how smaller-scale features affect the aggregate behavior at larger scales. We studied the effects on oil-sweep efficiency of the proportion, hierarchical organization, and connectivity of high-permeability open-framework conglomerate (OFC) cross-sets within the multi-scale stratal architecture found in fluvial deposits. We further analyzed oil production rate, water breakthrough time, and spatial and temporal distribution of residual oil saturation. As expected, the effective permeability of the reservoir exhibits large-scale anisotropy created by the organization of OFC cross-sets within unit bars, and the organization of unit bars within compound- bars. As a result, oil-sweep efficiency critically depends on the direction of the pressure gradient. However, contrary to expectations, the total amount of trapped oil due to the effect of capillary trapping does not depend on the magnitude of the pressure gradient within the examined range. Hence the pressure difference between production and injection wells does not affect sweep efficiency; although the spatial distribution of oil remaining in the reservoir depends on this value. Whether or not clusters of connected OFC span the domain affects only the absolute rate of oil production—not sweep efficiency.

58 GEOSCIENCES↗

Using Experiments to Build a Body of Knowledge

Experimentation in software engineering is important but difficult. One reason it is so difficult is that there are a large number of context variables, and so creating a cohesive understanding of experimental results requires a mechanism for motivating studies and integrating results. This paper argues for the necessity of a framework for organizing sets of related studies. With such a framework, experiments can be viewed as part of common families of studies, rather than being isolated events. Common families of studies can contribute to important and relevant hypotheses that may not be suggested by individual experiments. A framework also facilitates building knowledge in an incremental manner through the replication of experiments within families of studies. Building knowledge in this way requires a community of researchers that can replicate studies, vary context variables, and build abstract models that represent the common observations about the discipline. This paper also presents guidelines for lab packages, meant to encourage and support replications, that encapsulate materials, methods, and experiences concerning software engineering experiments.

Basili, Victor↗

Design and optimization of a modular hydrogen-based integrated energy system to maximize revenue via nuclear-renewable sources

Here, this paper demonstrates a novel modular distributed framework that uses optimal energy-dispatching strategies to enable greater flexibility and profitability in nuclear-renewable integrated energy systems (NR-IES). Hydrogen is used as a commodity in this framework since its production can improve grid stability and system operational flexibility, decarbonize heavy industry, and create an additional revenue stream for electricity generators, particularly nuclear power plants with high operational expenses. The proposed solution addresses the challenges associated with merging multiple software and services from various domains by using functional mock-up units (FMU) to co-simulate diverse subsystems designed in various platforms. The tightly coupled integrated energy system (IES) is optimized to maximize revenue by utilizing the deep reinforcement learning (DRL) technique to make smart dispatching decisions based on variable electricity prices and the availability of renewable energy. Proximal policy optimization (PPO) algorithm is used in training and testing the DRL agent. Over a period of 120 days, the proposed hydrogen-based IES framework showed about 10% revenue boost compared to a non-hydrogen generating baseline IES while also providing an easily-adoptable framework which can help to improve the flexibility of future generation nuclear power plants.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Dshell++: A Component Based, Reusable Space System Simulation Framework

This paper describes the multi-mission Dshell++ simulation framework for high fidelity, physics-based simulation of spacecraft, robotic manipulation and mobility systems. Dshell++ is a C++/Python library which uses modern script driven object-oriented techniques to allow component reuse and a dynamic run-time interface for complex, high-fidelity simulation of spacecraft and robotic systems. The goal of the Dshell++ architecture is to manage the inherent complexity of physicsbased simulations while supporting component model reuse across missions. The framework provides several features that support a large degree of simulation configurability and usability.

Software↗

Application-level regression testing framework using Jenkins

Monitoring and testing for regression of large-scale systems such as the NCSA's Blue Waters supercomputer are challenging tasks. In this paper, we describe the solution we came up with to perform those tasks. The goal was to find an automated solution for running user-level regression tests to evaluate system usability and performance. Jenkins, an automation server software, was chosen for its versatility, large user base, and multitude of plugins including collecting data and plotting test results over time. We also describe our Jenkins deployment to launch and monitor jobs on remote HPC system, perform authentication with one-time password, and integrate with our LDAP server for its authorization. We show some use cases and describe our best practices for successfully using Jenkins as a user-level system-wide regression testing and monitoring framework for large supercomputer systems.

97 MATHEMATICS AND COMPUTING↗

DFTB+, a software package for efficient approximate density functional theory based atomistic simulations

DFTB+ is a versatile community developed open source software package offering fast and efficient methods for carrying out atomistic quantum mechanical simulations. By implementing various methods approximating density functional theory (DFT), such as the density functional based tight binding (DFTB) and the extended tight binding method, it enables simulations of large systems and long timescales with reasonable accuracy while being considerably faster for typical simulations than the respective ab initio methods. Based on the DFTB framework, it additionally offers approximated versions of various DFT extensions including hybrid functionals, time dependent formalism for treating excited systems, electron transport using non-equilibrium Green’s functions, and many more. DFTB+ can be used as a user-friendly standalone application in addition to being embedded into other software packages as a library or acting as a calculation-server accessed by socket communication. We give an overview of the recently developed capabilities of the DFTB+ code, demonstrating with a few use case examples, discuss the strengths and weaknesses of the various features, and also discuss on-going developments and possible future perspectives.

74 ATOMIC AND MOLECULAR PHYSICS↗

A framework for building real-time expert systems

The Space Station Freedom is an example of complex systems that require both traditional and artificial intelligence (AI) real-time methodologies. It was mandated that Ada should be used for all new software development projects. The station also requires distributed processing. Catastrophic failures on the station can cause the transmission system to malfunction for a long period of time, during which ground-based expert systems cannot provide any assistance to the crisis situation on the station. This is even more critical for other NASA projects that would have longer transmission delays (e.g., the lunar base, Mars missions, etc.). To address these issues, a distributed agent architecture (DAA) is proposed that can support a variety of paradigms based on both traditional real-time computing and AI. The proposed testbed for DAA is an autonomous power expert (APEX) which is a real-time monitoring and diagnosis expert system for the electrical power distribution system of the space station.

Lee, S. Daniel↗

The Behavior, Constraint, and Scenario (BeCoS) Tool: A Web-Based Software Application for Modeling Behaviors and Scenarios

The Behavior, Constraint, and Scenario (BeCoS) tool has been developed to allow engineers to specify system and component behaviors. The tool is a web application that is developed in JavaScript and uses the React framework for the user interface and Redux for maintaining application state. The foundation of the tool is its underlying ontology, which expands upon a previously-defined behavior ontology with a scenario ontology. The behavior ontology includes elements like behaving elements, state variables, parameters, and constraints, while the scenario ontology includes core constructs like activities, temporal constraints, and timepoints. BeCoS allows users to easily create behaving elements and to specify their state variables, parameters, state machines, and constraints. BeCoS also allows users to develop temporal constraint networks that specify constraints on component states over time. BeCoS is a prototype tool that has been deployed and tested by systems engineers on the Europa Clipper project, which generated several use cases and helped steer its current developmental effort. By enabling systems engineers to specify behavior in a semantically-rigorous manner, BeCoS is an enabling technology for analyses that previously could not be performed, and when exporting its model to other tools, allows for consistent behavior models to be used.

Ingham, Michel D.↗