Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Software Framework”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SU-E-I-97: Smart Auto-Planning Framework in An EMR Environment (SAFEE)

Purpose: Our Radiation Oncology Department uses clinical practice guidelines for patient treatment, including normal tissue sparing and other dosimetric constraints. These practice guidelines were adapted from national guidelines, clinical trials, literature reviews, and practitioner's own experience. Modern treatment planning systems (TPS) have the capability of incorporating these practice guidelines to automatically create radiation therapy treatment plans with little human intervention. We are developing a software infrastructure to integrate clinical practice guidelines and radiation oncology electronic medical record (EMR) system into radiation therapy treatment planning system (TPS) for auto planning. Methods: Our Smart Auto-Planning Framework in an EMR environment (SAFEE) uses a software pipeline framework to integrate practice guidelines,EMR, and TPS together. The SAFEE system starts with retrieving diagnosis information and physician's prescription from the EMR system. After approval of contouring, SAFEE will automatically create plans according to our guidelines. Based on clinical objectives, SAFEE will automatically select treatment delivery techniques (such as, 3DRT/IMRT/VMAT) and optimize plans. When necessary, SAFEE will create multiple treatment plans with different combinations of parameters. SAFEE's pipeline structure makes it very flexible to integrate various techniques, such as, Model-Base Segmentation (MBS) and plan optimization algorithms, e.g., Multi-Criteria Optimization (MCO). In addition, SAFEE uses machine learning, data mining techniques, and an integrated database to create clinical knowledgebase and then answer clinical questions, such as, how to score plan quality or how volume overlap affects physicians' decision in beam and treatment technique selection. Results: In our institution, we use Varian Aria EMR system and RayStation TPS from RaySearch, whose ScriptService API allows control by external programs. These applications are the building blocks of our SAFEE system. Conclusion: SAFEE is a feasible method of integrating clinical information to develop an auto-planning paradigm to improve clinical workflow in cancer patient care.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

PRIME - A Software Toolkit for the Characterization of Partially Observed Epidemics in a Bayesian Framework

PRIME is a modeling framework designed for the “real-time’” characterization and forecasting of partially observed epidemics. Characterization is the estimation of infection spread parameters using daily counts of symptomatic patients. The method is designed to help guide medical resource allocation in the early epoch of the outbreak. The estimation problem is posed as one of Bayesian inference and solved using a Markov Chain Monte Carlo technique. The framework can accommodate multiple epidemic waves and can help identify different disease dynamics at the regional, state, and country levels. We include examples using publicly available COVID-19 data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2022

Application of Orthogonal Defect Classification for Software Reliability Analysis

The modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate reliability methodologies by both the United States (U.S.) Nuclear Regulatory Commission (NRC) and the industry. This has resulted in hesitation for further modernization projects until a more unified methodology is realized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) the potential failure modes of a DI&C software system. The semantic classification model is used to address the question: How do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: Given the connection between latent defects and software failure root causes, how can we quantify the reliability of the software? A case study was conducted on a representative I&C platform (ChibiOS) running a smart sensor acquisition software developed by Virginia Commonwealth University (VCU). The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine the software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify software reliability (or unreliability) while still leveraging the strength of the existing methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1986

Experimentation in software engineering

Experimentation in software engineering supports the advancement of the field through an iterative learning process. In this paper, a framework for analyzing most of the experimental work performed in software engineering over the past several years is presented. A variety of experiments in the framework is described and their contribution to the software engineering discipline is discussed. Some useful recommendations for the application of the experimental process in software engineering are included.

Basili, V. R.↗
DOE OSTI2022

SPEL: Software tool for Porting E3SM Land Model with OpenACC in a Function Unit Test Framework

Most high-end computers adopt hybrid architecture, porting a large-scale scientific code onto accelerators is necessary. The paper presents a generic method for porting large-scale scientific code onto accelerators using compiler directives within a modularized function unit test platform. We have implemented the method and designed a software tool (SPEL) to port the E3SM Land Model (ELM) onto the GPUs in the Summit computer. SPEL automatically generates GPU-ready test modules for all ELM functions, such as CanopyFlux, SoilTemperature, and EcosystemDynamics. SPEL breaks the ELM into a collection of standalone unit test programs for easy code verification and further performance improvement. We further optimize several ELM test modules with advanced techniques, including memory reduction, reconstructed parallel loops, and asynchronous GPU kernel launch. We hope our study will inspire new toolkit developments that expedite large-scale scientific code porting with compiler directives.

Schwartz, Peter↗
DOE OSTI2017

NIRP Core Software Suite v. 1.0

The NIRP Core Software Suite is a core set of code that supports multiple applications. It includes miscellaneous base code for data objects, mathematic equations, and user interface components; and the framework includes several fully-developed software applications that exist as stand-alone tools to compliment other applications. The stand-alone tools are described below. Analyst Manager: An application to manage contact information for people (analysts) that use the software products. This information is often included in generated reports and may be used to identify the owners of calculations. Radionuclide Viewer: An application for viewing the DCFPAK radiological data. Compliments the Mixture Manager tool. Mixture Manager: An application to create and manage radionuclides mixtures that are commonly used in other applications. High Explosive Manager: An application to manage explosives and their properties. Chart Viewer: An application to view charts of data (e.g. meteorology charts). Other applications may use this framework to create charts specific to their data needs.

Whitener, Dustin Heath↗
NASA NTRS2011

The Planning Execution Monitoring Architecture

The Planning Execution Monitoring (PEM) architecture is a design concept for developing autonomous cockpit command and control software. The PEM architecture is designed to reduce the operations costs in the space transportation system through the use of automation while improving safety and operability of the system. Specifically, the PEM autonomous framework enables automatic performance of many vehicle operations that would typically be performed by a human. Also, this framework supports varying levels of autonomous control, ranging from fully automatic to fully manual control. The PEM autonomous framework interfaces with the core flight software to perform flight procedures. It can either assist human operators in performing procedures or autonomously execute routine cockpit procedures based on the operational context. Most importantly, the PEM autonomous framework promotes and simplifies the capture, verification, and validation of the flight operations knowledge. Through a hierarchical decomposition of the domain knowledge, the vehicle command and control capabilities are divided into manageable functional "chunks" that can be captured and verified separately. These functional units, each of which has the responsibility to manage part of the vehicle command and control, are modular, re-usable, and extensible. Also, the functional units are self-contained and have the ability to plan and execute the necessary steps for accomplishing a task based upon the current mission state and available resources. The PEM architecture has potential for application outside the realm of spaceflight, including management of complex industrial processes, nuclear control, and control of complex vehicles such as submarines or unmanned air vehicles.

Wang, Lui↗
NASA NTRS2011

Image Segmentation, Registration, Compression, and Matching

A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity/topology components of the generated models. The highly efficient triangular mesh compression compacts the connectivity information at the rate of 1.5-4 bits per vertex (on average for triangle meshes), while reducing the 3D geometry by 40-50 percent. Finally, taking into consideration the characteristics of 3D terrain data, and using the innovative, regularized binary decomposition mesh modeling, a multistage, pattern-drive modeling, and compression technique has been developed to provide an effective framework for compressing digital elevation model (DEM) surfaces, high-resolution aerial imagery, and other types of NASA data.

Yadegar, Jacob↗
DOE OSTI2018

Implementation of ANL’s Mechanics Based Evolutionary Fatigue Modeling Through ABAQUS-WARP3D Based High-Performance Computing Framework

This report presents an update on the environmental fatigue research that is being conducted at Argonne National Laboratory in support of the Department of Energy’s Light Water Reactor Sustainability (LWRS) program. Argonne is developing a fully mechanistic fatigue evaluation approach without using empirical fatigue (S~N) curves. This approach is based on the fundamental concept of the time evolution of progressive fatigue damage rather than on the conventional S~N curve approaches using end-of-life data. In FY 2017, we performed extensive validation of this approach with respect to fatigue test data for 316 stainless steel [1]. This validation was performed for different loading cases, including constant, variable, and random amplitude. In the present FY 2018 semi-annual report, we present the further advances of Argonne’s environmental fatigue research work in the context for more practical applications. In this report, we discuss a methodology for fully mechanistic (i.e., not using S~N curves) fatigue life evaluation of reactor components subjected to realistic loading cycles, namely, design-basis loading cycles. The loading cycles include plant heat-up, full-power, and cool-down operations. As a test case, we considered a typical pressurized water reactor surge line, which is made of 316 SS. To perform the fatigue simulation for thousands of fatigue cycles in a computationally cost effective way, we modified our previous desktop-based finite element (FE) modeling approach to work in a high-performance computing (HPC) framework. For the HPC implementation, we developed a hybrid framework based on commercial FE software (ABAQUS), open-source FE software (WARP3D), and Argonne-developed evolutionary cyclic-plasticity modeling methods. We validated this HPC-based cycle-by-cycle damage model for the entire fatigue life of a Pressurized Water Reactor (PWR) surge line (SL) pipe with respect to assumed loading cycles. The simulated fatigue life was found to be 5855 cycles, which is 85% accurate as compared to the corresponding small-specimen-based experimental fatigue life (6914 cycles). Also, the simulated stress history captures the cyclic hardening and softening behavior of the material for entire fatigue cycles. The FE simulation of the PWR SL pipe was conducted in a reasonable time of 12.5 days. These results show the promise that a fully mechanistic (not using S~N curves) fatigue life evaluation of a safety-critical nuclear reactor component (or even other safety critical components like those in aircraft, aero-engines, etc.) is possible. We anticipate that this type of methodology will drastically reduce the uncertainly associated with conventional fatigue life estimates based on empirical S~N curves. We also proposed an FE model that is based on a hybrid full-component and single-element approach and that can readily be used by industry if HPC resources are not available. In this approach, a single-cycle FE simulation has to be performed first for the required loading cycle. Then, the resulting strain/stress profile at the hotspot (highest strain/stress location) is used as input strain/stress loading to the single-element FE model. The single-element FE model is run under multiple fatigue cycles as long as the failure criteria are achieved. The cycle number at failure gives the fatigue life of the component in question. This cost-effective framework does not require expensive HPC hardware and can be performed in a reasonable time by using a desktop computer. We demonstrated this approach with respect to PWR SL fatigue evaluation under two realistic design-basis loading cycles (simple and detailed). The associated results were validated with respect to test data obtained through fatigue testing of uniaxial specimens under the in-air condition at 300 °C. The approach is in the development stage and requires further improvement and validation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2001

Onyx-Advanced Aeropropulsion Simulation Framework Created

The Numerical Propulsion System Simulation (NPSS) project at the NASA Glenn Research Center is developing a new software environment for analyzing and designing aircraft engines and, eventually, space transportation systems. Its purpose is to dramatically reduce the time, effort, and expense necessary to design and test jet engines by creating sophisticated computer simulations of an aerospace object or system (refs. 1 and 2). Through a university grant as part of that effort, researchers at the University of Toledo have developed Onyx, an extensible Java-based (Sun Micro-systems, Inc.), objectoriented simulation framework, to investigate how advanced software design techniques can be successfully applied to aeropropulsion system simulation (refs. 3 and 4). The design of Onyx's architecture enables users to customize and extend the framework to add new functionality or adapt simulation behavior as required. It exploits object-oriented technologies, such as design patterns, domain frameworks, and software components, to develop a modular system in which users can dynamically replace components with others having different functionality.

Reed, John A.↗
NASA NTRS1994

Design document for the Surface Currents Data Base (SCDB) Management System (SCDBMS), version 1.0

The Surface Currents Database Management System (SCDBMS) provides access to the Surface Currents Data Base (SCDB) which is maintained by the Naval Oceanographic Office (NAVOCEANO). The SCDBMS incorporates database technology in providing seamless access to surface current data. The SCDBMS is an interactive software application with a graphical user interface (GUI) that supports user control of SCDBMS functional capabilities. The purpose of this document is to define and describe the structural framework and logistical design of the software components/units which are integrated into the major computer software configuration item (CSCI) identified as the SCDBMS, Version 1.0. The preliminary design is based on functional specifications and requirements identified in the governing Statement of Work prepared by the Naval Oceanographic Office (NAVOCEANO) and distributed as a request for proposal by the National Aeronautics and Space Administration (NASA).

Krisnnamagaru, Ramesh↗
NASA NTRS1994

Design document for the MOODS Data Management System (MDMS), version 1.0

The MOODS Data Management System (MDMS) provides access to the Master Oceanographic Observation Data Set (MOODS) which is maintained by the Naval Oceanographic Office (NAVOCEANO). The MDMS incorporates database technology in providing seamless access to parameter (temperature, salinity, soundspeed) vs. depth observational profile data. The MDMS is an interactive software application with a graphical user interface (GUI) that supports user control of MDMS functional capabilities. The purpose of this document is to define and describe the structural framework and logical design of the software components/units which are integrated into the major computer software configuration item (CSCI) identified as MDMS, Version 1.0. The preliminary design is based on functional specifications and requirements identified in the governing Statement of Work prepared by the Naval Oceanographic Office (NAVOCEANO) and distributed as a request for proposal by the National Aeronautics and Space Administration (NASA).

Source record↗
NASA NTRS2016

Technical Reference Suite Addressing Challenges of Providing Assurance for Fault Management Architectural Design

Research into complexities of software systems Fault Management (FM) and how architectural design decisions affect safety, preservation of assets, and maintenance of desired system functionality has coalesced into a technical reference (TR) suite that advances the provision of safety and mission assurance. The NASA Independent Verification and Validation (IV&V) Program, with Software Assurance Research Program support, extracted FM architectures across the IV&V portfolio to evaluate robustness, assess visibility for validation and test, and define software assurance methods applied to the architectures and designs. This investigation spanned IV&V projects with seven different primary developers, a wide range of sizes and complexities, and encompassed Deep Space Robotic, Human Spaceflight, and Earth Orbiter mission FM architectures. The initiative continues with an expansion of the TR suite to include Launch Vehicles, adding the benefit of investigating differences intrinsic to model-based FM architectures and insight into complexities of FM within an Agile software development environment, in order to improve awareness of how nontraditional processes affect FM architectural design and system health management. The identification of particular FM architectures, visibility, and associated IV&V techniques provides a TR suite that enables greater assurance that critical software systems will adequately protect against faults and respond to adverse conditions. Additionally, the role FM has with regard to strengthened security requirements, with potential to advance overall asset protection of flight software systems, is being addressed with the development of an adverse conditions database encompassing flight software vulnerabilities. Capitalizing on the established framework, this TR suite provides assurance capability for a variety of FM architectures and varied development approaches. Research results are being disseminated across NASA, other agencies, and the software community. This paper discusses the findings and TR suite informing the FM domain in best practices for FM architectural design, visibility observations, and methods employed for IV&V and mission assurance.

Fitz, Rhonda↗
NASA NTRS2017

Automated Analysis of Stateflow Models

Stateflow is a widely used modeling framework for embedded and cyber physical systems where control software interacts with physical processes. In this work, we present a framework a fully automated safety verification technique for Stateflow models. Our approach is two-folded: (i) we faithfully compile Stateflow models into hierarchical state machines, and (ii) we use automated logic-based verification engine to decide the validity of safety properties. The starting point of our approach is a denotational semantics of State flow. We propose a compilation process using continuation-passing style (CPS) denotational semantics. Our compilation technique preserves the structural and modal behavior of the system. The overall approach is implemented as an open source toolbox that can be integrated into the existing Mathworks Simulink Stateflow modeling framework. We present preliminary experimental evaluations that illustrate the effectiveness of our approach in code generation and safety verification of industrial scale Stateflow models.

Stateflow↗
NASA NTRS1988

Modernization of software quality assurance

The customers satisfaction depends not only on functional performance, it also depends on the quality characteristics of the software products. An examination of this quality aspect of software products will provide a clear, well defined framework for quality assurance functions, which improve the life-cycle activities of software development. Software developers must be aware of the following aspects which have been expressed by many quality experts: quality cannot be added on; the level of quality built into a program is a function of the quality attributes employed during the development process; and finally, quality must be managed. These concepts have guided our development of the following definition for a Software Quality Assurance function: Software Quality Assurance is a formal, planned approach of actions designed to evaluate the degree of an identifiable set of quality attributes present in all software systems and their products. This paper is an explanation of how this definition was developed and how it is used.

Bhaumik, Gokul↗
NASA NTRS2019

Software and System Health Management with R2U2

R2U2 (Realizable, Responsive, Unobtrusive Unit) is a hardware-supported tool and framework for the real-time system and software health management of cyber-physical systems. R2U2 continuously monitors properties about safety, performance, and security of the vehicle and can perform diagnostic reasoning. Efficient observers for past-time and future-time Metric Temporal Logic, reasoners for Bayesian Networks, and model-based prognostics algorithms are major components of R2U2. Their combination makes it possible to design powerful models for system runtime monitoring, diagnostics, software health management, prognostics, and security monitoring. The R2U2 monitoring engine is designed for minimal runtime overhead and is available as Simulink block or as a software component for integration into the flight software stack, and enables R2U2 to monitor complex cyber-physical systems without any instrumentation of the flight software. In this presentation, we give an overview of R2U2 architecture and reasoning algorithms, present its features, and give a life demo of the tool.

Schumann, Johann↗
DOE OSTI2019

A rigorous process modeling methodology for biomass fast pyrolysis with an entrained-flow reactor

A biomass fast pyrolysis model was developed for implementation in equation-oriented modeling software. Based on a previous framework of coupled 1-dimensional mass, momentum, and heat balance equations, this model includes updated reaction kinetics to provide a more detailed representation of biomass components, intermediates, and products. A recently published derivation of thermodynamic properties for the species in this model has allowed the energy balance around the pyrolysis reactor to be rigorously redefined. With these improvements, the optimum pyrolysis temperature for bio-oil production predicted by the model is increased by up to 50°C, bringing it in line with experimental data and increasing the overall agreement. More importantly, the reactor energy balance is strictly enforced. The resulting model can be used for the design and optimization of biomass fast pyrolysis processes, and comparisons with other options for biomass utilization.

09 BIOMASS FUELS↗