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At least 649 records · Page 36

A defense in depth approach for nuclear power plant accident management

An initiating event may lead to a severe accident if the plant safety functions have been challenged or operators do not follow the appropriate accident management procedures. Beyond design basis accidents are those corresponding to events of very low occurrence probability but such an accident may lead to significant consequences. The defense in depth approach is important to assure nuclear safety even in a severe accident. Plant Damage States (PDS) can be defined by the combination of the possible values for each of the PDS parameters which are showed on the nuclear power plant simulator. PDS is used to identify what the initiating event is, and can also give the information of safety system's status whether they are bypassed, inoperable or not. Initiating event and safety system's status are used in the construction of Containment Event Tree (CET) to determine containment failure modes by using probabilistic risk assessment (PRA) technique. Different initiating events will correspond to different CETs. With these CETs, the core melt frequency of an initiating event can be found. The use of Plant Damage States (PDS) is a symptom-oriented approach. On the other hand, the use of Containment Event Tree (CET) is an event-oriented approach. In this study, the Taiwan's fourth nuclear power plants, the Lungmen nuclear power station (LNPS), which is an advanced boiling water reactor (ABWR) with fully digitized instrumentation and control (I and C) system is chosen as the target plant. The LNPS full scope engineering simulator is used to generate the testing data for method development. The following common initiating events are considered in this study: loss of coolant accidents (LOCA), total loss of feedwater (TLOFW), loss of offsite power (LOOP), station blackout (SBO). Studies have indicated that the combination of the symptom-oriented approach and the event-oriented approach can be helpful to find mitigation strategies and is useful for the accident management. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Experimental validation of an organic rankine-vapor compression cooling cycle using low GWP refrigerant R1234ze(E)

There is a significant global opportunity to capture and utilize low grade waste heat to reduce fossil fuel consumption, greenhouse gas emissions, and improve energy efficiency across a wide range of industries. In this work, an advanced type of thermally activated cooling system, an organic Rankine-vapor compression cycle (ORVC) with novel heat integration strategies, was designed and tested at a relevant scale for industrial waste heat recovery (300 kW th cooling capacity). The ORVC linked an organic Rankine power cycle and a vapor compression cooling cycle using a turbine and compressor that shared a single shaft. The ORVC test facility absorbed waste heat from a liquid stream at 91 °C to simulate engine coolant in diesel generator sets, rejected heat to a glycol stream at 30 °C, and generated chilled water at 7 °C. A cooling capacity of 264 kW ± 3.5 kW was experimentally validated with a COP of 0.56 ± 0.01 during steady-state operation at the design temperatures. The thermal efficiency, accounting for pump work, of the Rankine cycle was 7.7% ± 0.22% and the COP of the vapor compression cycle was 5.25 ± 0.09. The centrifugal turbo-compressor operated at 31.5 kRPM ± 0.3 kRPM, with a turbine and compressor isentropic efficiencies of 76.7% ± 0.90% and 84.8% ± 0.54%, respectively, with near-perfect power transmission between these components. The pressure drop in the piping and heat exchangers were significantly larger than expected which had a detrimental impact on the performance of the ORVC. In addition, the condenser on the cooling cycle could not deliver the subcooling as specified from the design point modeling. Furthermore, the results from the sensitivity analysis showed that the higher condenser glycol outlet temperature had the largest impact on performance, which is consistent with other analytical models in the literature. When the ORVC simulations were updated with experimental values for isentropic efficiencies of the turbomachinery, the thermal COP was 0.66 which represents an estimate of the predicted performance if test facility limitations are overcome.

30 DIRECT ENERGY CONVERSION↗

Sintering and Fracture Behavior of Plasma-sprayed Thermal Barrier Coatings

Thermal barrier coatings will be more aggressively designed to protect gas turbine engine hot-section components in order to meet future engine higher fuel efficiency and lower emission goals. There is a need to characterize the fundamental sintering and fracture behavior of the current ZrO2-(7 to 8)wt%Y2O3 coating, in order to fully take advantage of the coating capability. In addition, a thorough evaluation of the coating behavior and temperature limits will be useful for more accurately assessing the benefit gained from future advanced coating systems. In this study, the sintering behavior of plasma-sprayed ZrO2-8wt%Y2O3 coatings was systematically investigated as a function of temperature and time using a dilatometer in the temperature range of 1200-1500 C. The coating sintering kinetics obtained by dilatometry were compared with the coating thermal conductivity increase kinetics, determined by a steady-state laser heat-flux testing approach, under high temperature and thermal gradient sintering conditions. The mode I, mode II, and mixed mode I-mode II fracture behavior of as-processed and sintering-annealed coatings was determined in asymmetric flexure loading at ambient and elevated temperatures in order to evaluate the coating sintering effects on the fracture envelope of K(sub I) versus K(sub II). The coating thermal conductivity cyclic response associated with the interface delamination of the coating systems under simulated engine heat-flux conditions will be discussed in conjunction with the sintering and fracture testing results.

Zhu, Dongming↗

Influence of NOx Chemistry on the Prediction of Natural Gas End-Gas Autoignition

Research on the influence of NOx (NO/NO2) chemistry on HC oxidation has shown that NOx plays an important role in the promotion/inhibition of HC autoignition [1-6]. Current data for n-heptane, iso-octane, ethanol, and toluene [3, 4] have shown that NO chemistry inhibits autoignition at low temperatures and concentrations. However, at medium and high temperatures and low concentrations, autoignition is promoted, decreasing the Negative Temperature Coefficient (NTC) effect. This autoignition promotion, however, becomes weaker as NO concentrations are increased. Additionally, fundamental kinetics studies have suggested that NOx chemistry also promotes the autoignition of smaller HC, such as CH4 [7-10], C2H6 [11-14], and C3H8 [15]. Additionally to the chemical kinetics studies, a growing body of evidence supports the importance of NOx chemistry on SI engine simulations [16, 17]. Foong et al. [18] suggested that the addition of NO in their models significantly improved the agreement between simulations and experiments where the onset of knock was advanced due to the presence of NO, and Morganti et al. [19] showed that NO addition in the residual-gas was necessary for their models to obtain good agreement with experimental data. Lastly, Mohr et al. [20, 21] investigated the effect of Natural Gas (NG) reactivity and EGR substitution rate and composition on homogeneous ignition delay, flame speeds, and EGAI for stoichiometric NG/oxidizer/EGR blends. They observed that the addition of EGR composed of only inert species (CO2 and Ar) suppressed homogeneous autoignition in all NG fuels tested under all conditions. However, for all NG fuels tested, increasing EGR rates with reactive species (Ar, CO2, CO, and NO) promoted homogeneous autoignition under all conditions, thus reproducing the same trends for various NG fuel compositions that were observed in other studies and fuels. For this reason, a study is being conducted to analyze the effects of NOx chemistry on the prediction of NG/air/EGR homogeneous autoignition. This study has been divided into two tasks. First, the addition of NOx chemistry to the ARIES82 mechanism [20] is being validated using homogeneous ignition delay data collected by Mohr [20, 21]. Second, once the new modified mechanism with NOx reactions has been validated, it will be employed on engine multi-dimensional modeling presented in [22, 23] to analyze the influence of NOx chemistry on NG EGAI. Results thus far have shown that homogeneous ignition delay calculations are sensitive to NOx chemistry, where the modified mechanisms captured well all trends and closely matched the homogeneous ignition delays observed by Mohr et al. Also, the results in this work suggest that NOx chemistry is necessary to correctly capture the trends in NG homogeneous autoignition when EGR with reactive species is used since the opposite behavior is observed when only inert species are considered for the EGR composition.

03 NATURAL GAS↗

Large liquid rocket engine transient performance simulation system

A simulation system, ROCETS, was designed and developed to allow cost-effective computer predictions of liquid rocket engine transient performance. The system allows a user to generate a simulation of any rocket engine configuration using component modules stored in a library through high-level input commands. The system library currently contains 24 component modules, 57 sub-modules and maps, and 33 system routines and utilities. FORTRAN models from other sources can be operated in the system upon inclusion of interface information on comment cards. Operation of the simulation is simplified for the user by run, execution, and output processors. The simulation system makes available steady-state trim balance, transient operation, and linear partial generation. The system utilizes a modern equation solver for efficient operation of the simulations. Transient integration methods include integral and differential forms for the trapezoidal, first order Gear, and second order Gear corrector equations. A detailed technology test bed engine (TTBE) model was generated to be used as the acceptance test of the simulation system. The general level of model detail was that reflected in the Space Shuttle Main Engine DTM. The model successfully obtained steady-state balance in main stage operation and simulated throttle transients, including engine starts and shutdown. A NASA FORTRAN control model was obtained, ROCETS interface installed in comment cards, and operated with the TTBE model in closed-loop transient mode.

Mason, J. R.↗

Documenting the NASA Armstrong Flight Research Center Oblate Earth Simulation Equations of Motion and Integration Algorithm

A desire for more complete documentation of the National Aeronautics and Space Administration (NASA) Armstrong Flight Research Center (AFRC), Edwards, California legacy code used in the core simulation has led to this e ort to fully document the oblate Earth six-degree-of-freedom equations of motion and integration algorithm. The authors of this report have taken much of the earlier work of the simulation engineering group and used it as a jumping-o point for this report. The largest addition this report makes is that each element of the equations of motion is traced back to first principles and at no point is the reader forced to take an equation on faith alone. There are no discoveries of previously unknown principles contained in this report; this report is a collection and presentation of textbook principles. The value of this report is that those textbook principles are herein documented in standard nomenclature that matches the form of the computer code DERIVC. Previous handwritten notes are much of the backbone of this work, however, in almost every area, derivations are explicitly shown to assure the reader that the equations which make up the oblate Earth version of the computer routine, DERIVC, are correct.

integrators↗

Verification of Data-Driven Models of Physical Phenomena using Interpretable Approximation

Machine-learned models, specifically neural networks, are increasingly used as “closures” or “constitutive models” in engineering simulators to represent fine-scale physical phenomena that are too computationally expensive to resolve explicitly. However, these neural net models of unresolved physical phenomena tend to fail unpredictably and are therefore not used in mission-critical simulations. In this report, we describe new methods to authenticate them, i.e., to determine the (physical) information content of their training datasets, qualify the scenarios where they may be used and to verify that the neural net, as trained, adhere to physics theory. We demonstrate these methods with neural net closure of turbulent phenomena used in Reynolds Averaged Navier-Stokes equations. We show the types of turbulent physics extant in our training datasets, and, using a test flow of an impinging jet, identify the exact locations where the neural network would be extrapolating i.e., where it would be used outside the feature-space where it was trained. Using Generalized Linear Mixed Models, we also generate explanations of the neural net (à la Local Interpretable Model agnostic Explanations) at prototypes placed in the training data and compare them with approximate analytical models from turbulence theory. Finally, we verify our findings by reproducing them using two different methods.

42 ENGINEERING↗

Progress of a Cross-Correlation Based Optical Strain Measurement Technique for Detecting Radial Growth on a Rotating Disk

The Aeronautical Sciences Project under NASA's Fundamental Aeronautics Program is interested in the development of novel measurement technologies, such as optical surface measurements for the in situ health monitoring of critical constituents of the internal flow path. In situ health monitoring has the potential to detect flaws, i.e. cracks in key components, such as engine turbine disks, before the flaws lead to catastrophic failure. The present study, aims to further validate and develop an optical strain measurement technique to measure the radial growth and strain field of an already cracked disk, mimicking the geometry of a sub-scale turbine engine disk, under loaded conditions in the NASA Glenn Research Center's High Precision Rotordynamics Laboratory. The technique offers potential fault detection by imaging an applied high-contrast random speckle pattern under unloaded and loaded conditions with a CCD camera. Spinning the cracked disk at high speeds (loaded conditions) induces an external load, resulting in a radial growth of the disk of approximately 50.0-μm in the flawed region and hence, a localized strain field. When imaging the cracked disk under static conditions, the disk will be undistorted; however, during rotation the cracked region will grow radially, thus causing the applied particle pattern to be 'shifted'. The resulting particle displacements between the two images is measured using the two-dimensional cross-correlation algorithms implemented in standard Particle Image Velocimetry (PIV) software to track the disk growth, which facilitates calculation of the localized strain field. A random particle distribution is adhered onto the surface of the cracked disk and two bench top experiments are carried out to evaluate the technique's ability to measure the induced particle displacements. The disk is shifted manually using a translation stage equipped with a fine micrometer and a hotplate is used to induce thermal growth of the disk, causing the particles to become shifted. For both experiments, reference and test images are acquired before and after the induced shifts, respectively, and then processed using PIV software. The controlled manual translation of the disk resulted in detection of the particle displacements accurate to ~1.75% of full scale and the thermal expansion experiment resulted in successful detection of the disk's thermal growth as compared to the calculated thermal expansion results. After validation of the technique through the induced shift experiments, the technique is implemented in the Rotordynamics Lab for preliminary assessment in a simulated engine environment. The discussion of the findings and plans for future work to improve upon the results are addressed in the paper.

rotordynamics↗

SU-E-T-523: On the Radiobiological Impact of Lateral Scatter in Proton Beams

Introduction: In proton therapy, justified concern has been voiced with respect to an increased efficiency in cell kill at the distal end of the Bragg peak. This coupled with range uncertainty is a counter indication to use the Bragg peak to define the border of a treated volume with a critical organ. An alternative is to use the lateral edge of the proton beam, obtaining more robust plans. We investigate the spectral and biological effects of the lateral scatter . Methods: A general purpose Monte Carlo simulation engine (MCNPX 2.7c) installed on a Scientific Linux cluster, calculated the dose deposition spectrum of protons, knock on electrons and generated neutrons for a proton beam with maximal kinetic energy of 200MeV. Around the beam at different positions in the beam direction the spectrum is calculated in concentric rings of thickness 1cm. The deposited dose is converted to a double strand break map using an analytical expression.based on micro dosimetric calculations using a phenomenological Monte Carlo code (MCDS). A strict version of RBE is defined as the ratio of generation of double strand breaks in the different modalities. To generate the reference a Varian linac was modelled in MCNPX and the generated electron dose deposition spectrum was used . Results: On a pristine point source 200MeV beam the RBE before the Bragg peak was of the order of 1.1, increasing to 1.7 right behind the Bragg peak. When using a physically more realistic beam of 10cm diameter the effect was smaller. Both the lateral dose and RBE increased with increasing beam depth, generating a dose deposition with mixed biological effect. Conclusions: The dose deposition in proton beams need to be carefully examined because the biological effect will be different depending on the treatment geometry. Deeply penetrating proton beams generate more biologically effective lateral scatter.

07 ISOTOPE AND RADIATION SOURCES↗

ActiveSpaces: Exploring dynamic code deployment for extreme scale data processing: ActiveSpaces: Exploring dynamic code deployment for extreme scale data processing

Managing the large volumes of data produced by emerging scientific and engineering simulations running on leadership-class resources has become a critical challenge. The data have to be extracted off the computing nodes and transported to consumer nodes so that it can be processed, analyzed, visualized, archived, and so on. Several recent research efforts have addressed data-related challenges at different levels. One attractive approach is to offload expensive input/output operations to a smaller set of dedicated computing nodes known as a staging area. However, even using this approach, the data still have to be moved from the staging area to consumer nodes for processing, which continues to be a bottleneck. In this paper, we investigate an alternate approach, namely moving the data-processing code to the staging area instead of moving the data to the data-processing code. Specifically, we describe the ActiveSpaces framework, which provides (1) programming support for defining the data-processing routines to be downloaded to the staging area and (2) runtime mechanisms for transporting codes associated with these routines to the staging area, executing the routines on the nodes that are part of the staging area, and returning the results. We also present an experimental performance evaluation of ActiveSpaces using applications running on the Cray XT5 at Oak Ridge National Laboratory. Finally, we use a coupled fusion application workflow to explore the trade-offs between transporting data and transporting the code required for data processing during coupling, and we characterize sweet spots for each option.

97 MATHEMATICS AND COMPUTING↗

Performance model-directed data sieving for high-performance I/O

Many scientific computing applications and engineering simulations exhibit noncontiguous I/O access patterns. Data sieving is an important technique to improve the performance of noncontiguous I/O accesses by combining small and noncontiguous requests into a large and contiguous request. It has been proven effective even though more data are potentially accessed than demanded. In this study, we propose a new data sieving approach namely performance model-directed data sieving, or PMD data sieving in short. It improves the existing data sieving approach from two aspects: (1) dynamically determines when it is beneficial to perform data sieving; and (2) dynamically determines how to perform data sieving if beneficial. It improves the performance of the existing data sieving approach considerably and reduces the memory consumption as verified by both theoretical analysis and experimental results. Given the importance of supporting noncontiguous accesses effectively and reducing the memory pressure in a large-scale system, the proposed PMD data sieving approach in this research holds a great promise and will have an impact on high-performance I/O systems.

97 MATHEMATICS AND COMPUTING↗

Enhancing EnergyPlus capabilities to model dynamic building envelopes using python plugin

Nearly half of the energy consumption in the United States is related to buildings, resulting in an urgent need to develop innovative technologies to improve building energy efficiency. Dynamic building envelopes, comprising switchable insulation and thermal energy storage materials, have been proposed recently as a promising solution to reduce buildings' heating and cooling loads by thermally coupling the indoor environment with the ambient environment when beneficial while decoupling them when outdoor conditions are not favorable. Although various related technologies are still underway, the whole-building energy modeling tools, like EnergyPlus, do not have the capability to simulate the transient and dynamic nature of dynamic envelope materials and components to accurately predict their impact on building energy use. The objective of this study is to formulate a method in EnergyPlus simulation engine to model multilayer envelopes, comprising dynamic building materials with variable thermophysical properties, and discuss the changes made to the program using a Python plugin. Furthermore, the thermal performance of the dynamic envelopes using the proposed method is compared and verified with the results from a well-established commercial code, COMSOL Multiphysics. A parametric assessment is also conducted to evaluate the energy efficiency benefits of dynamic envelopes in a single-family residential building, demonstrating total annual energy savings up to 11.6 %, when a dynamic envelope operates alone, and up to 18.2 % when it is combined with a thin layer of phase change material as a thermal storage medium. Finally, a United States wide energy efficiency assessment is presented to showcase the geographical spread of the energy savings. The method designed and implemented in this study provides the researchers with the ability to implement their dynamic insulation methods in EnergyPlus and evaluate the whole building energy impact.

25 ENERGY STORAGE↗

Scaling relation for high-temperature biodiesel surrogate ignition delay times

High-temperature Arrhenius ignition delay time correlations are useful for revealing the underlying parameter dependencies of combustion models, for simplifying and optimizing combustion mechanisms for use in engine simulations, for scaling experimental data to new conditions for comparison purposes, and for guiding in experimental design. Here, we have developed a scaling relationship for Fatty Acid Methyl Ester (FAME) ignition time data taken at high temperatures in 4%O 2 /Ar mixtures behind reflected shocks using an aerosol shock tube: τ ign [ms] = 2.24 x 10 -6 [ms] (P [atm]) -.41 ($\phi$) 0.30 (C n ) -.61 x exp $$ \left(\frac{37.1 [kcal/mol]}{\hat{R}_u [kcal / mol K] T [K]}\right) $$ In addition, we have combined our ignition delay time data for methyl decanoate, methyl palmitate, methyl oleate, and methyl linoleate with other experimental results in the literature in order to derive fuel-specific oxygen-mole-fraction scaling parameters for these surrogates. In conclusion, in this article, we discuss the significance of the parameter values, compare our correlation to others found in the literature for different classes of fuels, and contrast the above expression’s performance with correlations obtained using leading FAME kinetic models in 4%O 2 /Ar mixtures.

09 BIOMASS FUELS↗

Large scale centrifuge test of a geomembrane-lined landfill subject to waste settlement and seismic loading

Highlights: • A large centrifuge model of a geomembrane-lined landfill was seismically loaded. • The scaled peak acceleration of the strongest input motion was 0.6 g. • Laboratory testing was conducted to obtain properties of the model materials. • Collected data included liner strains due to downdrag and seismic loading. • Results show that settlement and seismic loading can potentially damage geomembranes. • Results can be used to validate numerical models for geomembrane performance. •The laboratory and centrifuge testing data is publicly available. - Abstract: A large scale centrifuge test of a geomembrane-lined landfill subject to waste settlement and seismic loading was conducted to help validate a numerical model for performance based design of geomembrane liner systems. The test was conducted using the 240 g-ton centrifuge at the University of California at Davis under the U.S. National Science Foundation Network for Earthquake Engineering Simulation Research (NEESR) program. A 0.05 mm thin film membrane was used to model the liner. The waste was modeled using a peat-sand mixture. The side slope membrane was underlain by lubricated low density polyethylene to maximize the difference between the interface shear strength on the top and bottom of the geomembrane and the induced tension in it. Instrumentation included thin film strain gages to monitor geomembrane strains and accelerometers to monitor seismic excitation. The model was subjected to an input design motion intended to simulate strong ground motion from the 1994 Hyogo-ken Nanbu earthquake. Results indicate that downdrag waste settlement and seismic loading together, and possibly each phenomenon individually, can induce potentially damaging tensile strains in geomembrane liners. The data collected from this test is publically available and can be used to validate numerical models for the performance of geomembrane liner systems.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Probing the Chemical Kinetics of Minimalist Functional Group Gasoline Surrogates

We report surrogate mixtures are routinely used for understanding gasoline fuel combustion in engine simulations. The general trend in surrogate formulation has been to increase the number of fuel components in a mixture to better emulate real fuel properties. Recently, a new surrogate design strategy based on functional group analysis of real gasolines was proposed using a minimal number of species [minimalist functional group (MFG)-approach]. MFG surrogates (having just one or two components) could experimentally capture the ignition delay time (IDT), threshold sooting index, and smoke point of different gasoline fuels with hundreds of components. However, other combustion characteristics were not explored, and kinetic modeling of MFG surrogates was not reported. These aspects are addressed in this paper, where the combustion behavior of MFG surrogates for various gasolines was assessed by simulating IDT, jet-stirred reactor oxidation, and premixed laminar flame speeds using chemical kinetic modeling. MFG simulations were compared with experimental data of the real gasolines as well as with the more complex multicomponent (five to nine species) surrogates. This study reveals that binary MFG surrogate mixtures are capable of accurately simulating the combustion behavior of more complex gasoline fuels with hundreds of components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

GQLink: an implementation of Quantized State Systems (QSS) methods in Geant4

Simulations in high energy physics (HEP) often require the numerical solution of ordinary differential equations (ODE) to determine the trajectories of charged particles in a magnetic field when particles move throughout detector volumes. Each crossing of a volume interrupts the underlying numerical method that solves the equations of motion, triggering iterative algorithms to estimate the intersection point within a given accuracy. The computational cost of this procedure can grow significantly depending on the application at hand. Quantized State System (QSS) is a recent family of discrete-event driven numerical methods exhibiting attractive features for this type of problems, such as native dense output (sequences of polynomial segments updated only by accuracy-driven events) and lightweight detection and handling of volume crossings. In this work we present GQLink, a proof-of-concept integration of QSS with the Geant4 simulation toolkit which stands as an interface for co-simulation that orchestrates robustly and transparently the interaction between the QSS simulation engine and aspects such as geometry definition and physics processes controlled by Geant4. In conclusion, we validate the accuracy and study the performance of the method in simple geometries (subject to intense volume crossing activity) and then in a realistic HEP application using a full CMS detector configuration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Neural Network Molecular Dynamics at Scale

Neural network molecular dynamics (NNMD) simulations could revolutionize atomistic modeling of materials with quantum-mechanical accuracy at a fraction of computational cost. However, popular NNMD frameworks are generally implemented for a single computing node, and conventional energy-based NN models still suffer from large time-to-solution (T2S), prohibiting the application of NNMD to challenging materials simulations encompassing large spatiotemporal scales. Consequently, no leadership-scale NNMD simulation has thus far been reported. Here, we present a scalable parallel NNMD software (RXMD-NN) based on our scalable reactive molecular dynamics simulation engine named RXMD. RXMD-NN has achieved high scalability up to 786,432 IBM BlueGene/Q cores involving 1.7 billion atoms. Furthermore, we have achieved 4.6-fold reduction of T2S by using a novel network that directly predicts atomic forces from feature vectors. Reduced T2S has for the first time allowed the study of large-scale off-stoichiometry effect in a widely used phase change material, Ge 2 Se 2 Te 5 , thereby resolving its "firstsharp diffraction peak mystery".

fist sharp diffraction peak↗

A Faster-Than-Real-Time Framework for Reliability-Oriented Simulation of PV Inverters

Physics-of-Failure (PoF) based reliability assessment for photovoltaic (PV) inverters requires long-duration electrical and electrothermal stress histories, yet generating such stress histories with high-fidelity switching models over year long mission profiles is computationally prohibitive. Conventional methods either sacrifice modeling fidelity for speed or require runtimes that are impractical for design iteration and uncertainty studies. To address this bottleneck, this paper presents a High-Performance Computing (HPC) based simulation frame work for faster-than-real-time reliability-oriented simulation. The proposed framework integrates the Average-to-Switching (A2S) method with parallel computing techniques to accelerate switching-level waveform reconstruction. We further introduce optimization strategies, including cluster merging and sensitivity based mission profile screening, to reduce the computational burden. Evaluated using real-world mission profile inputs and a MATLAB/Simulink switching-model reference, the framework reduces the simulation time for a one-year mission from an intractable multi-year duration to approximately 7.3 minutes while maintaining low waveform error. This acceleration provides a practical reliability-oriented simulation engine that can be coupled with component-specific aging models for subsequent PV inverter PoF assessment.

High-performance Computing↗