N&R develops sophisticated engineering software tools for its clients that generally enable high-fidelity simulation of complex systems. On occasion, simpler tools are developed such as first-order reliability estimation via Excel spreadsheets. C/C++ and Fortran are the typical programming languages, using Microsoft Windows or Unix/Linux operating systems.
If you are interested in learning more about these programs, please feel free to contact us!
Probabilistic Structural and Thermal Analysis Code (NESTEM)
The NESTEM code is a combination of a heat transfer analysis program (CSTEM), a constituent-level ceramic material composite code (CEMCAN), and a NASA-sponsored probabilistic structural analysis code called NESSUS (Numerical Evaluation of Stochastic Structures Under Stress). NESTEM can be used to analyze complex ceramic composite combustors and other high-temperature/high-stress aerospace components subject to modeling uncertainties. It can handle heat transfer uncertainties and composite material uncertainties as well as loading, material, and boundary condition uncertainties. It can generate a geometric model of simple structures or, alternatively, accept the geometric models generated by ANSYS or NASTRAN. In addition to enabling probabilistic heat-transfer analysis, NESTEM makes it possible to generate mathematical models of components by use of selected modules from the NASA Composite Blade Structural Analyzer (COBSTRAN) computer code. N&R also interfaced NESSUS with NASA’s Quantitative Risk Assessment System code (QRAS).
Systems Uncertainty Analysis (SUA)
The SUA tool we developed performs probabilistic analyses of systems of components, each of which are represented by analytic models with uncertainties. The component models are generally legacy physics-based deterministic simulation codes arbitrarily selected by the user. Hence, users may use codes they are familiar with rather than attempting to learn new codes with their associated learning curves. An example problem concerning the Space Shuttle’s main engine illustrates its value. The three LOX/LH2 rocket engines each depend upon 4 primary turbopumps in a complex high-temperature/high-stress environment. In order to maintain adequate thrust, the control system may increase the turbine inlet temperatures to mitigate component performance shortfalls or other deficiencies. But raising the turbine inlet temperature to compensate for such variations also consumes turbine life quickly. Hence, it is important to determine how much impact on turbine life (and therefore risk) is present due to these uncertainties. In the example problem, 13 uncertainties were identified and the deterministic ROCETS code was used in conjunction with SUA to determine the impact of these uncertainties on turbine inlet temperature. The SUA results are presented to the user graphically with CDF and PDF curves that convey the system-level impact of the 13 uncertainties. SUA also displays a probabilistic sensitivity factor chart that identifies the most important uncertainties. In this case, the two most important uncertainties are the high-pressure fuel pump efficiency (ETAMHPFP) and the high-pressure fuel turbine efficiency (ETAHMHPFT). Armed with this knowledge, program managers can take the most effective preventive actions to avoid serious operational risks.
Probabilistic Design and Analysis Framework (PRODAF)
PRODAF is a suite of software tools that are used to integrate user-supplied simulation codes into a probabilistic design/analysis system. It allows system-level reliability constraints to impact component-level designs and interfaces user-selected, physics-based deterministic modeling codes with a Fast Probability Integration code to obtain high-fidelity probabilistic component failure rate data. The computed component failure rates are input into a system-level probabilistic risk assessment code such as QRAS or SAPHIRE. A feedback loop from the risk assessment tool to the analysis/design tools enables the system-level reliability constraint to affect the component design. Accuracy measures of the probability calculations (confidence intervals) are provided to account for uncertainties in the uncertainty parameters. Design variable optimization is accelerated through the use of adaptive response surface modeling.
Foreign Object Damage and Identification (FODID)
N&R developed a real-time fault detection/diagnostic code (FODID) that utilizes a weighted least-squares methodology to identify faults such as foreign object damage (FOD) and determine which components are damaged and how severely. This tool performs both a gas path analysis and a structural vibration analysis, and then fuses the resulting data using fuzzy logic to provide a more confident solution than relying on either detection methodology alone.
Composite Blade Structural Analyzer (COBSTRAN)
COBSTRAN (COmposite Blade STRuctural ANalyzer) is a computer code designed to carry out the many linear analyses required to efficiently model and analyze blade-like structural components made of multilayered angle-plied fiber composites. Inputs to COBSTRAN are composite constituent fiber and matrix material properties, factors reflecting the fabrication process, composite geometry and model geometry. COBSTRAN determines the ply layup at each grid point and calculates the equivalent homogeneous properties at each grid point. Outputs are the individual ply properties and nodal composite properties consisting of membrane, bending and coupling stiffnesses. Also, finite element structural analysis grid, connectivity and material data are generated. COBSTRAN generates model finite element data in formats compatible with COSMIC NASTRAN and MSC/NASTRAN.
Electrical Power System for the International Space Station – Probabilistic Analysis of Power Supply
N&R has performed a number of probabilistic analyses of complex engineering systems with uncertainties identified at the component level. For example, our NASA-sponsored study investigated the impact of sub-system uncertainties and environmental uncertainties in the electrical power system of the International Space Station. The uncertainties included the Earth’s albedo, the space station’s positional altitude, battery capacity, the DC/DC converter efficiency, and the battery charge/discharge unit efficiency. The analysis results gave program managers a quantitative perspective on the available electrical power to be expected, accounting for these uncertainties.
Probabilistic Structural Analysis of Jupiter Orbiter Mission
The N&R generic Systems Uncertainty Analysis (SUA) code was used in conjunction with the NASA NBODY code to perform a probabilistic analysis of a 1200-day solar-electric powered Jupiter orbiter mission. Payload ratio was determined subject to various uncertainties in system parameters such as structural weight, thruster efficiency, and propulsion system weight.