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HyRAM is a software toolkit for conducting quantitative risk assessment (QRA) and consequence modeling for hydrogen infrastructure and transportation systems. HyRAM contains validated, simplified hydrogen behavior models, a standardized QRA approach, and engineering models and generic data relevant to hydrogen installations. HyRAM 1.0 was developed by Sandia National Laboratories for the U. S. Department of Energy. SAND2019-5270 M
Reactive burn models represent a significant leap in high explosive (HE) modeling capability. The first generation of engineering models of HE detonation are called programmed burn models and they are largely based on the distance between a prescribed detonation point and each zone in a simulation. There have been many advancements to programmed burn models over the years and when the assumptions upon which they are based are met, a properly tuned programmed burn model can be highly accurate but if any of their assumptions is not met, as is the case for corner turning or weakly initiated HE burn, they will give the wrong answer. Reactive burn models represent an entirely new way of modeling HE burn. They use the local conditions of a zone – e.g. temperature, pressure or density – as calculated by a hydrocode to determine if and when the zone is going to detonate and if so, how rapidly. This difference opens up an entirely new set of capabilities for HE modeling. It makes it possible to accurately and predictively model phenomena like the effect of confinement and the formation of dead zones. Reactive burn models have seen sustained development effort at LANL for at least the last decade but several recent developments make it timely to transition reactive burn models from a research topic to a production tool. The main goal of this milestone is to facilitate and accelerate the adoption of reactive burn as a commonly available modeling option, with recommendations on the resolution that will be required and uncertainties associated with their modeling choices. To achieve this, we have performed verification, validation, and uncertainty quantification (UQ) assessments of AWSD and SURF/SURFplus in xRage and FLAG on a variety of different problems.
The basic goal was to advance the development status of the 30-cm electron bombardment ion thruster from a laboratory model to a flight-type engineering model (EM) thruster. This advancement included the more conventional aspects of mechanical design and testing for launch loads, weight reduction, fabrication process development, reliability and quality assurance, and interface definition, as well as a relatively significant improvement in thruster total efficiency. The achievement of this goal was demonstrated by the successful completion of a series of performance and structural integrity (vibration) tests. In the course of the program, essentially every part and feature of the original 30-cm Thruster was critically evaluated. These evaluations, led to new or improved designs for the ion optical system, discharge chamber, cathode isolator vaporizer assembly, main isolator vaporizer assembly, neutralizer assembly, packaging for thermal control, electrical terminations and structure.
The value of early flight evaluation of propulsion and propulsion control concepts was demonstrated on the NASA F-15 airplane in programs such as highly integrated digital electronic control (HIDEC), the F100 engine model derivative (EMD), and digital electronic engine control (DEEC). (In each case, the value of flight demonstration was conclusively demonstrated). This paper described these programs, and discusses the results that were not expected, based on ground test or analytical prediction. The role of flight demonstration in facilitating transfer of technology from the laboratory to operational airplanes is discussed.
The value of early flight evaluation of propulsion and propulsion control concepts was demonstrated on the NASA F-15 airplane in programs such as highly integrated digital electronic control (HIDEC), the F100 engine model derivative (EMD), and digital electronic engine control (DEEC). (In each case, the value of flight demonstration was conclusively demonstrated.) This paper describes these programs, and discusses the results that were not expected, based on ground test or analytical prediction. The role of flight demonstration in facilitating transfer of technology from the laboratory to operational airplanes is discussed.
Direct thrust measurement using strain gages offers advantages over analytically-based thrust calculation methods. For flight test applications, the direct measurement method typically uses a simpler sensor arrangement and minimal data processing compared to analytical techniques, which normally require costly engine modeling and multisensor arrangements throughout the engine. Conversely, direct thrust measurement has historically produced less than desirable accuracy because of difficulty in mounting and calibrating the strain gages and the inability to account for secondary forces that influence the thrust reading at the engine mounts. Consequently, the strain-gage technique has normally been used for simple engine arrangements and primarily in the subsonic speed range. This paper presents the results of a strain gage-based direct thrust-measurement technique developed by the NASA Dryden Flight Research Center and successfully applied to the full flight envelope of an F-15 aircraft powered by two F100-PW-229 turbofan engines. Measurements have been obtained at quasi-steady-state operating conditions at maximum non-augmented and maximum augmented power throughout the altitude range of the vehicle and to a maximum speed of Mach 2.0 and are compared against results from two analytically-based thrust calculation methods. The strain-gage installation and calibration processes are also described.
The thermal decomposition of ammonium perchlorate (AP) and ammonium-perchlorate-based composite propellants is studied using the simultaneous thermogravimetric modulated beam mass spectrometry (STMBMS) technique. The main objective of the present work is to evaluate whether the STMBMS can provide new data on these materials that will have sufficient detail on the reaction mechanisms and associated reaction kinetics to permit creation of a detailed model of the thermal decomposition process. Such a model is a necessary ingredient to engineering models of ignition and slow-cookoff for these AP-based composite propellants. Results show that the decomposition of pure AP is controlled by two processes. One occurs at lower temperatures (240 to 270 C), produces mainly H2O, O2, Cl2, N2O and HCl, and is shown to occur in the solid phase within the AP particles. 200(micro) diameter AP particles undergo 25% decomposition in the solid phase, whereas 20(micro) diameter AP particles undergo only 13% decomposition. The second process is dissociative sublimation of AP to NH3 + HClO4 followed by the decomposition of, and reaction between, these two products in the gas phase. The dissociative sublimation process occurs over the entire temperature range of AP decomposition, but only becomes dominant at temperatures above those for the solid-phase decomposition. AP-based composite propellants are used extensively in both small tactical rocket motors and large strategic rocket systems.
Damaged aircraft have occasionally had to rely solely on thrust to maneuver as a consequence of losing hydraulic power needed to operate flight control surfaces. The lack of successful landings in these cases inspired research into more effective methods of utilizing propulsion-only control. That research demonstrated that one of the major contributors to the difficulty in landing is the slow response of the engines as compared to using traditional flight control. To address this, research is being conducted into ways of making the engine more responsive under emergency conditions. This can be achieved by relaxing controller limits, adjusting schedules, and/or redesigning the regulators to increase bandwidth. Any of these methods can enable faster response at the potential expense of engine life and increased likelihood of stall. However, an example sensitivity analysis revealed a complex interaction of the limits and the difficulty in predicting the way to achieve the fastest response. The sensitivity analysis was performed on a realistic engine model, and demonstrated that significantly faster engine response can be achieved compared to standard Bill of Material control. However, the example indicates the need for an intelligent approach to controller limit adjustment in order for the potential to be fulfilled.
Preliminary results from the Heavily Instrumented ALF503R-5 Engine test conducted in the NASA Glenn Research Center Propulsion Systems Laboratory will be discussed. The effects of ice crystal icing on a full scale engine is examined and documented. This model engine, serial number LF01, was used during the inaugural icing test in the PSL facility. The reduction of thrust (rollback) events experienced by this engine in flight were replicated in the facility. Limited instrumentation was used to detect icing. Metal temperature on the exit guide vanes and outer shroud and the load measurement were the only indicators of ice formation. The current study features a similar engine, serial number LF11, which is instrumented to characterize the cloud entering the engine, detect characterize ice accretion, and visualize the ice accretion in the region of interest.
Modern space systems are increasing in complexity and scale at an unprecedented pace. Consequently, innovative methods, processes, and tools are needed to cope with the increasing complexity of architecting these systems. A key systems challenge in practice is the ability to scale processes, methods, and tools used to architect complex space systems. Traditionally, the process for specifying space system architectures has largely relied on capturing the system architecture in informal descriptions that are often embedded within loosely coupled design documents and domain expertise. Such informal descriptions often lead to misunderstandings between design teams, ambiguous specifications, difficulty in maintaining consistency as the architecture evolves throughout the system development life cycle, and costly design iterations. Therefore, traditional methods are becoming increasingly inefficient to cope with ever-increasing system complexity. We apply the principles of component-based design and platform-based design to the development of the system architecture for a practical space system to demonstrate feasibility of our approach using SysML. Our results show that we are able to apply a systematic design method to manage system complexity, thus enabling effective data management, semantic coherence and traceability across different levels of abstraction in the design chain. Just as important, our approach enables interoperability among heterogeneous tools in a concurrent engineering model based design environment.
Estimate the mass of the Thermal Protection System (TPS) for a single design construct of an atmospheric entry probe with a rigid aeroshell, which could be used at five destinations, i.e. Venus, Saturn, Uranus, Neptune, and perhaps, Jupiter. The entry mass of the probe is 400 kg with a ballistic coefficient of 216 kg/m2. Process: The 3DoF trajectory simulation program Traj, coupled with the TPS response program FIAT was used for simulation and design. The assumed atmospheric models were VIRA (Venus-GRAM) for Venus, the Julianne Moses' model for Saturn, a NASA Ames engineering model for Uranus, Neptune-GRAM for Neptune, and Galileo Probe (Al Seiff's) result for Jupiter.
In this paper, the modelled debris fluxes by ESA’s Meteoroid And Space debris Terrestrial Environment Reference (MASTER-8) model and NASA’s Orbital Debris Engineering Model (ORDEM) 3.1 are compared. At first, the basic modelling approaches for both models are presented to explain the fundamentally different model philosophies and help the reader to comprehend and interpret the obtained results. Then, the flux results of both models for three different orbits are presented and analysed. They are discussed and set into perspective. A conclusion is drawn at the end of the paper, highlighting the ongoing cooperation of both agencies responsible for their models.
HyRAM is a software toolkit for conducting quantitative risk assessment (QRA) and consequence modeling for hydrogen infrastructure and transportation systems. HyRAM contains validated, simplified hydrogen behavior models, a standardized QRA approach, and engineering models and generic data relevant to hydrogen installations. HyRAM 1.0 was developed by Sandia National Laboratories for the U. S. Department of Energy to increase access to technical data about hydrogen and to enable the use of that data to support development and revision of national and international codes and standards with risk assessment and consequence modeling. The HyRAM toolkit integrates analytical and probabilistic models for quantifying accident scenarios, predicting physical effects, and characterizing the impact of hydrogen hazards (including thermal effects from jet fires and overpressure effects from deflagrations in confined areas) on people and structures. HyRAM incorporates generic probabilities for equipment failures for nine types of components, and probabilistic models for the impact of heat flux on humans and structures, with computationally and experimentally validated analytical first order models of hydrogen release and flame physics. Version 1 can be used to quantify the risk and consequences associated with gaseous hydrogen releases from user-defined hydrogen installations.
Grizzly is a simulation tool being developed at Idaho National Laboratory (INL) as part of the US Department of Energy’s Light Water Reactor Sustainability program to provide improved safety assessments of systems, components, and structures in nuclear power plants subjected to age-related degradation. Its goal is to provide an improved scientific basis for decisions surrounding license renewal, which would permit operation of commercial nuclear power plants beyond 60 years. Grizzly is based on INL’s MOOSE framework, which enables multiphysics simulations in a parallel computing environment. It will address a wide variety of aging issues in nuclear power plant systems, components, and structures, modelling both the aging processes and the ability of age-degraded components to perform safely. The reactor pressure vessel (RPV) was chosen as the initial application for Grizzly. Grizzly solves tightly coupled equations of heat conduction and solid mechanics to simulate the global response of the RPV to accident conditions, and uses submodels to represent regions with pre-existing flaws. Domain integrals are used to calculate stress intensity factors on those flaws. A physically based empirical model is used to evaluate material embrittlement, and is used to evaluate whether crack growth would occur. Grizzly can represent the RPV in 2D or 3D, allowing it to evaluate effects that require higher dimensionality models to capture. Work is underway to use lower length scale models of material evolution to inform engineering models of embrittlement. This paper demonstrates an application of Grizzly to RPV failure assessment, and summarizes on-going work.
We present that analytics software is increasingly used to improve and maintain operational efficiency in commercial buildings. Energy managers, owners, and operators are using a diversity of commercial offerings often referred to as Energy Information Systems, Fault Detection and Diagnostic (FDD) systems, or more broadly Energy Management and Information Systems, to cost-effectively enable savings on the order of ten to twenty percent. Most of these systems use data from meters and sensors, with rule-based and/or data-driven models to characterize system and building behavior. In contrast, physics-based modeling uses first-principles and engineering models (e.g., efficiency curves) to characterize system and building behavior. Historically, these physics-based approaches have been used in the design phase of the building life cycle or in retrofit analyses. Researchers have begun exploring the benefits of integrating physics-based models with operational data analytics tools, bridging the gap between design and operations. In this paper, we detail the development and operator use of a software tool that uses hybrid data-driven and physics-based approaches to cooling plant FDD and optimization. Specifically, we describe the system architecture, models, and FDD and optimization algorithms; advantages and disadvantages with respect to purely data-driven approaches; and practical implications for scaling and replicating these techniques. Finally, we conclude with an evaluation of the future potential for such tools and future research opportunities.
Modelling and simulation are essential parts in the study of dynamic systems behaviours. In nuclear engineering, modelling and simulation are important to assess the expected results of an experiment before the actual experiment is conducted or in the design of nuclear facilities. In education, modelling can give insight into the dynamic of systems and processes. Most nuclear processes can be described by ordinary or partial differential equations. Efforts expended to solve the equations using analytical or numerical solutions consume time and distract attention from the objectives of modelling itself. This paper presents the use of Simulink, a MATLAB toolbox software that is widely used in control engineering, as a modelling platform for the study of nuclear processes including nuclear reactor behaviours. Starting from the describing equations, Simulink models for heat transfer, radionuclide decay process, delayed neutrons effect, reactor point kinetic equations with delayed neutron groups, and the effect of temperature feedback are used as examples.
The Software Engineering Process Simulation (SEPS) model is described which was developed at JPL. SEPS is a dynamic simulation model of the software project development process. It uses the feedback principles of system dynamics to simulate the dynamic interactions among various software life cycle development activities and management decision making processes. The model is designed to be a planning tool to examine tradeoffs of cost, schedule, and functionality, and to test the implications of different managerial policies on a project's outcome. Furthermore, SEPS will enable software managers to gain a better understanding of the dynamics of software project development and perform postmodern assessments.
Psychological approach to human operator engineering models in manual control