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Results for “software reliability software”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Louisiana Immersive Technologies Enterprise (LITE): Enabling Coastal Stewardship and Reliable Energy
This project will focus on research and application development in the area of large scale data computing and visualization that are critical to the DoE BER program areas of climate change research, environmental sciences, life sciences, and medical sciences. Most commercial applications available today are unable to handle the sizes of data in these domains, usually in the order of terabytes and petabytes. This project will address this problem, by taking advantage of the advanced scientific computing infrastructure of the LITE and LONI to conduct research and develop software applications that run natively on these 64-bit supercomputing platforms. The project is consistent with the goals of Scientific Discovery through Advanced Computing (SciDAC), a DoE initiative.
54 ENVIRONMENTAL SCIENCES↗
Power Electronics Manufacturing Improvements for Heavy-Duty Fuel Cell Vehicles
The Marel Power Solutions project, funded by the U.S. Department of Energy under Award DE-SC0023801, focused on advancing manufacturing techniques for power electronics in heavy-duty fuel cell vehicles. The research aimed to enhance system efficiency, reduce costs, and support broader adoption of hydrogen fuel cell technology. Key areas of investigation included power topology, thermal modeling, system architecture, and accessibility through software tools. Key Accomplishments: 1. Power Topology: - Developed an interleaved boost converter with optimized phase count, leveraging Marel’s proprietary Power Stacks. - Achieved reduced parasitic inductance and resistance, enabling high efficiency in DC-DC converters. 2. Thermal Modeling: - Integrated innovative cooling systems into compact Silicon Carbide (SiC) modules. - Simulations demonstrated the ability to dissipate significant heat (up to 7.5 kW), ensuring device reliability under heavy loads. 3. System Architecture: - Utilized simulation tools to analyze the impact of various fuel cell and vehicle parameters on efficiency. - Highlighted the role of smaller, modular improvements, such as enhanced DC-DC converters, in achieving system-wide gains. 4. Accessibility: - Evaluated and implemented MATLAB/Simulink code generation tools for real-world hardware applications. - Demonstrated the potential for rapid prototyping of custom power systems with reduced development costs. Impact and Benefits: - Efficiency and Cost Reduction: Marel’s cooling technology enhances SiC die performance, reducing the number of dies required and overall system size. - Scalability and Flexibility: The innovations support tailored solutions for diverse applications, from mass transit to mining vehicles. - Sustainability: The research promotes the integration of electrification technologies, helping meet rising energy demands sustainably. Conclusion: The project’s outcomes advance the state of power electronics for hydrogen fuel cell vehicles, enabling more efficient, compact, and cost-effective solutions. These developments lay a foundation for future innovation, contributing to the broader adoption of clean energy technologies in transportation and other industries.
08 HYDROGEN↗
A Case Study of the Glycoside Hydrolase Enzyme Mechanism Using an Automated QM-Cluster Model Building Toolkit
Glycoside hydrolase enzymes are important for hydrolyzing the β-1,4 glycosidic bond in polysaccharides for deconstruction of carbohydrates. The two-step retaining reaction mechanism of Glycoside Hydrolase Family 7 (GH7) was explored with different sized QM-cluster models built by the Residue Interaction Network ResidUe Selector (RINRUS) software using both the wild-type protein and its E217Q mutant. The first step is the glycosylation, in which the acidic residue 217 donates a proton to the glycosidic oxygen leading to bond cleavage. In the subsequent deglycosylation step, one water molecule migrates into the active site and attacks the anomeric carbon. Residue interaction-based QM-cluster models lead to reliable structural and energetic results for proposed glycoside hydrolase mechanisms. The free energies of activation for glycosylation in the largest QM-cluster models were predicted to be 19.5 and 31.4 kcal mol −1 for the wild-type protein and its E217Q mutant, which agree with experimental trends that mutation of the acidic residue Glu217 to Gln will slow down the reaction; and are higher in free energy than the deglycosylation transition states (13.8 and 25.5 kcal mol −1 for the wild-type protein and its mutant, respectively). For the mutated protein, glycosylation led to a low-energy product. This thermodynamic sink may correspond to the intermediate state which was isolated in the X-ray crystal structure. Hence, the glycosylation is validated to be the rate-limiting step in both the wild-type and mutated enzyme.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Efficient Implementation of Artificial Neural Networks for Sensor Data Analysis Based on a Genetic Algorithm
The reliability of many industrial processes depends on the sensor system. However, these sensors can be affected by noise, perturbations and failures. Hence, sensor monitoring and diagnosis are fundamental to guarantee the quality of an industrial process. Nowadays, artificial neural networks (ANN) are widely used in sensor signal processing and diagnosis. However, those ANNs usually require many artificial neurons, being difficult to implement in software and hardware due to their high computational costs. This paper presents an optimized implementation of artificial neurons in ANNs for sensor data analysis using a Genetic Algorithm (GA). The objective of GA is to find an adequate segmentation to reduce the activation function approximation error. One of the advantages of the proposed approach is that the cost function used in GA considers the effect of factors such as the ANN architecture or the number of bits used in arithmetic operations. The proposed ANN implementation technique aims to get the best possible approximation for a specific ANN architecture, making easier its implementation in software and hardware. Simulation and experimental results using FPGA (Field Programmable Gate Array) prove the advantages of the proposed approach for implementing sensor data analysis systems based on ANNs.
D estefani, André↗
wtDigiTwin (Wind Turbine Digital Twin) [SWR-21-15]
This wind turbine digital twin software (wtDigiTwin) provides a digital twin solution for wind turbine applications. The focus of wtDigiTwin is to estimate loads, motions and environmental conditions for an operating wind turbine. The program uses supervisory control and data acquisition (SCADA) measurements as inputs, together with a wind turbine model. The wind industry is currently challenged by the high cost of operation and maintenance. These costs could be mitigated if component failures are predicted, but such predictions are difficult unless the turbines are equipped with expensive measuring devices. The alternative is to use a digital twin such as wtDigiTwin to estimate the necessary signals. wtDigiTwin can perform online prediction of signals that are otherwise not measured, using a limited set of reliable measurements and a physics-based model. The predicted signals can be used in applications that have direct cost benefits: 1) real-time estimation of the fatigue consumption of key components of the wind turbine; 2) root cause analyses and failure detections ; 3) lifetime reassessments ; 4) improvements to follow-on designs. The current version provides examples to estimate wind speed, thrust, torque, tower-top position, and tower loads on an onshore wind turbine using the following measurements tower top acceleration, generator torque, pitch, and rotational speed. The model combines a linear state-space model, a wind speed estimator, and a Kalman filter algorithm that integrates measurements with the state model to perform state estimations. The state space model is obtained either using OpenFAST linearizations, or using the yams package provided with the software.
Branlard, Emmanuel↗
De novo design and Rosetta-based assessment of high-affinity antibody variable regions (Fv) against the SARS-CoV -2 spike receptor binding domain ( RBD )
The continued emergence of new SARS-CoV-2 variants has accentuated the growing need for fast and reliable methods for the design of potentially neutralizing antibodies (Abs) to counter immune evasion by the virus. Here, we report on the de novo computational design of high-affinity Ab variable regions (Fv) through the recombination of VDJ genes targeting the most solvent-exposed hACE2-binding residues of the SARS-CoV-2 spike receptor binding domain (RBD) protein using the software tool OptMAVEn-2.0. Subsequently, we carried out computational affinity maturation of the designed variable regions through amino acid substitutions for improved binding with the target epitope. Immunogenicity of designs was restricted by preferring designs that match sequences from a 9-mer library of “human Abs” based on a human string content score. We generated 106 different antibody designs and reported in detail on the top five that trade-off the greatest computational binding affinity for the RBD with human string content scores. We further describe computational evaluation of the top five designs produced by OptMAVEn-2.0 using a Rosetta-based approach. We used Rosetta SnugDock for local docking of the designs to evaluate their potential to bind the spike RBD and performed “forward folding” with DeepAb to assess their potential to fold into the designed structures. Ultimately, our results identified one designed Ab variable region, P1.D1, as a particularly promising candidate for experimental testing. This effort puts forth a computational workflow for the de novo design and evaluation of Abs that can quickly be adapted to target spike epitopes of emerging SARS-CoV-2 variants or other antigenic targets.
59 BASIC BIOLOGICAL SCIENCES↗
The Emerging Interdependence of the Electric Power Grid & Information and Communication Technology
This paper examines the implications of emerging interdependencies between the electric power grid and Information and Communication Technology (ICT). Over the past two decades, electricity and ICT infrastructure have become increasingly interdependent, driven by a combination of factors including advances in sensor, network and software technologies and progress in their deployment, the need to provide increasing levels of wide-area situational awareness regarding grid conditions, and the promise of enhanced operational efficiencies. Grid operators’ ability to utilize new and closer-to-real-time data generated by sensors throughout the system is providing early returns, particularly with respect to management of the transmission system for purposes of reliability, coordination, congestion management, and integration of variable electricity resources such as wind generation.
24 POWER TRANSMISSION AND DISTRIBUTION↗
ESTIMATION OF THE WAKEFIELD RESONANT FREQUENCY USING DIFFERENT SIMULATION TOOLS
Reliable and fast wakefield calculations are important for beam dynamics and THz generation in accelerators. We compare approaches and limitations with different available simulation tools and compare results. As an example, we analyse a cylindrical corrugated waveguide with narrower and wider radii of 5 and 6 mm, and aperture width and periodicity of 1 and 2 mm using ABCI by KEK and ANSYS HFSS simulation software. First, ABCI was used to determine the resonant frequency of the cylindri-cal corrugated waveguide with different lengths. The corresponding results were taken as a reference to exam-ine the simulation method in the ANSYS HFSS environ-ment. The eigenmode solver of ANSYS HFSS was used to determine different resonant frequencies. This was fol-lowed by examining a cylindrical corrugated waveguide that was implemented having a length of 17 mm for dif-ferent conductor settings. The corresponding waveguide was fed by a plane wave having a resonant frequency that satisfies the intersection of the light line and dispersion curve of the corresponding mode. The analysis showed that the maximum loss factor was achieved at 39.20 and 40.07 GHz using ANSYS HFSS simulation data for differ-ent conductors, whereas ABCI resulted in 38.50 GHz. The talk will present the results gathered by different simula-tion setups implemented in ANSYS HFSS.
Unutmaz, Muhammed [SLAC National Accelerator Labor↗
An Open Source Extensible Smart Energy Framework
Aggregated distributed energy resources are the subject of much interest in the energy industry and are expected to play an important role in meeting our future energy needs by changing how we use, distribute and generate electricity. This energy future includes an increased amount of energy from renewable resources, load management techniques to improve resiliency and reliability, and distributed energy storage and generation capabilities that can be managed to meet the needs of the grid as well as individual customers. These energy assets are commonly referred to as Distributed Energy Resources (DER). DERs rely on a means to communicate information between an energy provider and multitudes of devices. Today DER control systems are typically vendor-specific, using custom hardware and software solutions. As a result, customers are locked into communication transport protocols, applications, tools, and data formats. Today’s systems are often difficult to extend to meet new application requirements, resulting in stranded assets when business requirements or energy management models evolve. By partnering with industry advisors and researchers, an implementation DER research platform was developed called the Smart Energy Framework (SEF). The hypothesis of this research was that an open source Internet of Things (IoT) framework could play a role in creating a commodity-based eco-system for DER assets that would reduce costs and provide interoperable products. SEF is based on the AllJoynTM IoT open source framework. The demonstration system incorporated DER assets, specifically batteries and smart water heaters. To verify the behavior of the distributed system, models of water heaters and batteries were also developed. An IoT interface for communicating between the assets and a control server was defined. This interface supports a series of “events” and telemetry reporting, similar to those defined by current smart grid communication standards. The results of this effort demonstrated the feasibility and application potential of using IoT frameworks for the creation of commodity-based DER systems. All of the identified commodity-based system requirements were met by the AllJoyn framework. By having commodity solutions, small vendors can enter the market and the cost of implementation for all parties is reduced. Utilities and aggregators can choose from multiple interoperable products reducing the risk of stranded assets. Based on this research it is recommended that interfaces based on existing smart grid communication protocol standards be created for these emerging IoT frameworks. These interfaces should be standardized as part of the IoT framework allowing for interoperability testing and certification. Similarly, IoT frameworks are introducing application level security. This type of security is needed for protecting application and platforms and will be important moving forward. Recommendations are that along with DER-based data model interfaces, platform and application security requirements also be prescribed when IoT devices support DER applications.
25 ENERGY STORAGE↗
Developing a Supply Chain Security Program
Amid growing concerns over foreign manufacturing for components and devices deployed in critical energy infrastructure, this research from the national labs will highlight best practices for developing and maintaining a supply chain security program. Tools for asset inventory, tips for developing and maintaining software- and hardware-bills-of-materials (SBOMs and HBOMs), recommended contractual language for vendor agreements, and identification of responsibilities will be shared. We discuss the one-time requirements to enable a successful supply chain security program and the best ways to operationalize this program for maximum impact, including development of robust practices for vulnerability tracking, patch management, and workarounds, with understanding of the reliability and uptime requirements for utilities. The recommendations shared are based on a cyber-informed engineering approach to identification of high-consequence impacts and the engineering controls related to supply chain management that can best mitigate these impacts. This approach allows for prioritization of resources. Additionally, we highlight relative up-front and ongoing costs associated with recommended controls. Viewers will leave with an understanding what a supply chain security program is, and what steps, prioritized for resource-constrained organizations, can build a robust program.
14 SOLAR ENERGY↗
Simulation studies on the standing and traveling wave thermoacoustic prime movers
Thermoacoustic systems have been a focus of recent research due to its structural simplicity, high reliability due to absence of moving parts, and can be driven by low grade energy such as fuel, gas, solar energy, waste heat etc. There has been extensive research on both standing wave and traveling wave systems. Towards the development of such systems, simulations can be carried out by several methods such as (a) solving the energy equation, (b) enthalpy flow model, (c) DeltaEC, a free software available from LANL, USA (d) Computational Fluid Dynamics (CFD) etc. We present here the simulation studies of standing wave and traveling wave thermoacoustic prime movers using CFD and DeltaEC. The CFD analysis is carried out using Fluent 6.3.26, incorporating the necessary boundary conditions with different working fluids at different operating pressures. The results obtained by CFD are compared with those obtained using DeltaEC. Also, the CFD simulation of the thermoacoustically driven refrigerator is presented.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Contact-Less Integrity Verification of Microelectronics Using Near-Field EM Analysis
Modern microelectronics life-cycle and supply chain ecosystem bring multiple untrusted entities, which can compromise their integrity. A major integrity issue of microelectronics stems from piracy of intellectual properties (IP) and counterfeiting, which causes significant revenue loss to the semiconductor manufacturers. Further, these components often lead to compromised functionality, reliability, security, and safety of an electronic system. This paper presents secure information transmission and probing methods for verifying the integrity of digital integrated circuit (ICs) based on their electromagnetic (EM) near-field emissions and thereby protecting systems against counterfeit components. The proposed method has been tested on both high-level instructions executed by microprocessors or Systems-on-Chip (serving as examples of software), and also logic circuits within FPGA fabrics and ASICs (serving as examples of hardware). The authentication information required by each digital system is generated using a pseudo-random number generator circuit and securely transmitted via near-field magnetic emissions. The authorized party can probe these emissions using a near-field probe, process the acquired signals to improve the signal-to-noise ratio (SNR), and then recover the secure information through matched filtering. Experimental results from commercial SoCs are used to demonstrate the proposed technique. Methods for reducing EM interference during integrity verification of both FPGAs and ASICs are also described.
47 OTHER INSTRUMENTATION↗
Smart building management vs. intuitive human control—Lessons learnt from an office building in Hungary
We report that smart building management and control are adopted nowadays to achieve zero-net energy use in buildings. However, without considering the human dimension, technologies alone do not necessarily guarantee high performance in buildings. An office building was designed and built according to state-of-the-art design and energy management principles in 2008. Despite the expectations of high performance, the owner was facing high utility bills and low user comfort in the building located in Budapest, Hungary. The objective of the project was to evaluate the energy performance and comfort indices of the building, to identify the causes of malfunction and to elaborate a comprehensive energy concept. Firstly, current building conditions and operation parameters were evaluated. Our investigation found that the state-of-the-art building management system was in good conditions but it was operated by building operators and occupants who are not aware of the building management practice. The energy consumption patterns of the building were simulated with energy modelling software. The baseline model was calibrated to annual measured energy consumption, using actual occupant behaviour and presence, based on results of self-reported surveys, occupancy sensors and fan-coil usage data. Realistic occupant behaviour models can capture diversity of occupant behaviour and better represent the real energy use of the building. This way our findings and the effect of our proposed improvements could be more reliable. As part of our final comprehensive energy concept, we proposed intervention measures that would increase indoor thermal comfort and decrease energy consumption of the building. A parametric study was carried out to evaluate and quantify energy, comfort and return on investment of each measure. It was found that in the best case the building could save 23% of annual energy use. Lastly, future work includes the follow-up of: occupant reactions to intervention measures, the realized energy savings, the measurement of occupant satisfaction and behavioural changes.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Phoebe: a high-performance framework for solving phonon and electron Boltzmann transport equations
Understanding the electrical and thermal transport properties of materials is critical to the design of electronics, sensors, and energy conversion devices. Computational modeling can accurately predict material properties but, in order to be reliable, requires accurate descriptions of electron and phonon states and their interactions. While first-principles methods are capable of describing the energy spectrum of each carrier, using them to compute transport properties is still a formidable task, both computationally demanding and memory intensive, requiring integration of fine microscopic scattering details for estimation of macroscopic transport properties. To address this challenge, we present Phoebe—a newly developed software package that includes the effects of electron–phonon, phonon–phonon, boundary, and isotope scattering in computations of electrical and thermal transport properties of materials with a variety of available methods and approximations. This open source C++ code combines MPI-OpenMP hybrid parallelization with GPU acceleration and distributed memory structures to manage computational cost, allowing Phoebe to effectively take advantage of contemporary computing infrastructures. We demonstrate that Phoebe accurately and efficiently predicts a wide range of transport properties, opening avenues for accelerated computational analysis of complex crystals.
36 MATERIALS SCIENCE↗
System Modeling Frameworks for Wind Turbines and Plants: Review and Requirements Specifications
System modeling frameworks for wind turbines and plants are used by research groups and industry to design wind energy systems that take into account key trade-offs across performance, cost, and reliability at both the turbine and plant level. The frameworks are exercised using a variety of multi-disciplinary design, analysis and optimization (MDAO) methods. To improve inter-operability and foster collaboration, this report proposes a classification system for the frameworks along dimensions of model fidelity and scope. The classification system is first motivated with reviews the state-of-the-art in the development of software frameworks for integrated wind turbine and plant simulation. Within each major wind turbine and power plant subsystem, a matrix is developed for the disciplines used and the fidelity levels with which each discipline can be modeled. The existing frameworks are then classified according to the matrix. Next, an ontology is proposed that will allow for standardizing how data is transferred between the most common discipline-fidelity combinations used in the frameworks. A common representation of data creates the ability to 1) share system descriptions and analysis results, supporting more transparent benchmarks and comparison, and 2) integrate models together into workflows within and across organizations for improving the efficiency and performance of wind turbine and power plant design processes. Ultimately, this integration leads to better overall wind energy system designs with high performance and low costs.
17 WIND ENERGY↗
Nailing the Peak: City-Scale, Building-Specific Load Factor and Contribution to a Utility’s Hour of Critical Generation
Maintaining electrical generation assets to meet peak demand increases the cost of providing electricity to a country’s buildings and insufficient assets can result in power outages. In order to keep reliable electricity costs low for consumers and demand charges low for utilities, there exist markets and financial incentives for limiting consumption during peak demand.The team has partnered with an electrical distributor servicing a 1,390 km2 area and 178,368 buildings with the aim of using urban-scale building energy modelling to inform business decisions necessary for the operation of their electric grid. A suite of software has been developed that allows the scalable creation of a “digital twin” for all buildings in the utility’s service area. This virtual utility area is analysed for targeted deployment of new technologies or policies to assess building-specific savings, effects on critically-loaded grid infrastructure (e.g. feeders, substations), and aggregated impact to utility-scale operations.This work leverages 15-minute data from each building to compare actual and simulated monthly peak-hour demand and assessment of the load factor for each building. Findings include market characterization via clustering of relative energy use profiles for ~180,000 buildings as well as simulation-informed savings opportunities indicating residential load factors of 0.17, commercial load factors of 0.2-0.4 depending on year of construction, and general load factors of 0.16-0.5 depending on building type.
New, Joshua↗
Utilizing the SACADA system to collect simulator training data to inform human reliability analyses - 169
Lack of appropriate human performance data for the development of human reliability analysis (HRA) methods has been identified as a key issue contributing to the method-to-method variability among the HRA methods. The United States Nuclear Regulatory Commission (NRC) worked with domain experts to develop the Scenario Authoring, Characterization, and Debriefing Application (SACADA) system to collect nuclear power plants' licensed operator simulator training and examination data to inform HRA. In the past two decades, significant improvements in understanding and modelling human performance in HRA have affected the perspectives of the types of data to be collected for HRA. A significant change is that human performance is strongly dependent on the context of the tasks to be performed. To incorporate this understanding, the SACADA data taxonomy collects the context and actual performance information of the training objective elements (TOEs) in nuclear plant operator simulator training. This provides a framework consistent with HRA to use context to estimate human error probabilities. It is recognized that measuring crew performance is equally important as improving operator training. SACADA is designed to support the nuclear trainers in capturing this important information that is used to identify training weaknesses and drive continuous improvement. This paper discusses the SACADA taxonomy, the SACADA system's functions, and the supporting software design to enable the SACADA system to be practically implemented in the nuclear power plants' operator simulator training program to collect data for tracking operator performance and HRA analysis. (authors)
22 GENERAL STUDIES OF NUCLEAR REACTORS↗