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At least 973 records · Page 54

High Energy Yield Distributed Architecture for Large Commercial and Utility-Scale PV Systems

Photovoltaic energy has come a long way from its early days when small cells were fabricated in the labs in the early 50s. While it took a long time for PV modules to mature into what we now see in the market and in rooftops across the world, the power electronics has been lagging behind & was always the weakest point in the PV plant, being responsible for the majority of failures & robbing the PV plants of their full potential by losing precious Watts in the process of converting power from DC to AC. Since the early days of PV power, it has been recognized that the modules need to operate at their maximum power point in order to extract as much power as is available from the PV modules at a given time of day and year. Numerous maximum power point devices were developed to do just this. While effective at extracting as much power as they can, soon after there was a realization that in a PV installation where a central inverter is used, many losses occur, hence energy yield losses. This has led to thinking about alternative architectures where the maximum power point tracking (MPPT) is performed much closer to the modules rather than at a central inverter. Several architectures were proposed ranging from a microinverter, microconverter, string inverter, string optimizer, and to a multi-string inverter or optimizer. While these architectures promise to increase the energy yield by 5% to 25% (depending where MPPT is located), & recovering losses due to shading, soiling, mismatch … there were no real studies and implementations in the field to corroborate these numbers. The program that GE Global Research proposed & received funding for is aimed at a type of distributed architectures, namely the dc architectures where only the MPPT function is distributed across the PV plant. Further, the project is concerned with choosing the right architecture for large scale commercial & utility scale plants but not residential installations. Findings from Task 1- Define Requirements & Develop Architecture- showed that for large scale commercial & utility PV plants, locating the MPPT at the string level with a string size of >3kW is the most cost effective solution & that the increase in energy yield of 6% to 8% is more than enough to make up for the increased cost due to additional power electronics. Our study also shows that in addition to an increase in energy yield, having a dc/dc converter at the string level brings additional benefits such as increased array visibility, allowing for increased monitoring and diagnostics; high and constant dc bus voltage which allows for reducing losses further and optimizing the inverter; and ability to detect ground and arc faults. Task 2 focused on designing a suitable dc/dc converter that meets the requirements defined in Task 1: Efficiency, Cost, & Reliability. For this task, we surveyed and simulated all candidate topologies known by the practitioners in the field. We also generated a novel topology, simulated it, & compared it to existing topologies. Our novel topology being a partial power processing converter came out on top due to its simplicity (fewer parts), it high efficiency, its reliability, and its lower cost. In the remaining tasks of the project, we built the hardware, tested it first in the lab, then in the field and once we worked out all the bugs and issues and were confident our system was robust, we installed it on the rooftop and started collecting the data by mid-Q3 2012. We shared our work with the scientific community in the form of conference & Journal papers, hence contributing to the general understanding of this technology area. The methods, techniques, and hardware developed under this project have all been tested in the field over long periods of time, and under many conditions and have been shown to be robust and reliable. The converters built and developed under this program have been in operation in the field since mid-June 2012, and no hardware failures have been recorded. While some software issues have been seen, none have been showstoppers. The cost analysis of the hardware showed that it meets the cost target set in the requirement document developed in the trade-off study. Improving the performance of solar installations for commercial and utility scale plants contributes to reducing their cost of ownership, hence spreading them to a larger section of the society and making them affordable. Our project contributed to the understanding of the distributed architectures, showed that PV plants’ cost of electricity can be reduced through additional power electronics which allows for harvesting more energy from the plant. When the project started in 2009, the cost of PV energy was still high, hence there was a real need to increase the energy yield, hence reduce the levelized cost of electricity (LCOE). While costs have come down significantly, the need for increasing the energy yield is still relevant, hence the project results, hardware, and techniques developed are still pertinent today. By taking this project from concept to rooftop demonstration, we showed that the technology is mature enough, robust enough, and has the potential to be used by many more customers, hence benefiting the public in general through the spread of PV energy, which ultimately contributes to reducing our dependency on fossil fuel, improving the environment, and creating more jobs.

14 SOLAR ENERGY↗

Evaluating the Impact of Off-Design CHP Performance on the Optimal Sizing and Dispatch on Hybrid Renewable-CHP Distributed Energy Resources

The maturation of distributed energy resources (DER) has prompted the exploration of their deployment in commercial building applications due to their potential to supply energy at lower costs and emissions rates compared to centralized generation. While several software tools exist for evaluating the techno-economic potential of integrated renewable energy and combined heat and power (CHP) systems for distributed generation applications, many suffer from poor accuracy in capturing off-design (part load and changes in ambient air temperature and pressure) performance characteristics of microturbines, combustion turbines, or internal combustion engines. Thus, this paper presents a methodology for integrating these off-design characteristics in the mixed-integer linear program within REopt, a hybrid DER screening tool. The economic impact of the CHP off-design performance is observed through several application studies of various hybrid system configurations in different climates. Each study indicates how CHP off-design performance influences optimal sizing and dispatch decisions and therefore overall system economic value. We observe through case studies that modeling without the off-design effects, depending on the CHP prime mover and site, can result in Net Present Value predictions of hybrid systems that can be overoptimistic in frequently hot climates (up to 52%), too conservative in frequently cold climates (up to 11%), or unaffected (+/-1%) in temperate climates. Cases also highlight several advantages of hybrid systems relative to non-hybrid systems such as total economic value and the systems' ability to mitigate potentially negative consequences attributed to off-design performance.

ambient de-rate↗

SU-G-IeP2-03: Comparison of Dose Calculation On MAR (metal Artifact Reduction) and Non-MAR Datasets for Pelvic Patients with Hip Prosthesis and Head and Neck Patients with Dental Filling

Purpose: Metal artifact reduction (MAR) software in computed tomography (CT) was previously evaluated with phantoms demonstrating the algorithm is capable of reducing metal artifacts without affecting the overall image quality. The goal of this study is to determine the dosimetric impact when calculating with CT datasets reconstructed with and without MAR software. Methods: Twelve head and neck cancer patients with dental fillings and four pelvic cancer patients with hip prosthesis were scanned with a GE Optima RT 580 CT scanner. Images were reconstructed with and without the MAR software. 6MV IMRT and VMAT plans were calculated with AAA on the MAR dataset until all constraints met our clinic’s guidelines. Contours from the MAR dataset were copied to the non-MAR dataset. Next, dose calculation on the non-MAR dataset was performed using the same field arrangements and fluence as the MAR plan. Conformality index, D99% and V100% to PTV were compared between MAR and non-MAR plans. Results: Differences between MAR and non-MAR plans were evaluated. For head and neck plans, the largest variations in conformality index, D99% and V100% were −3.8%, −0.9% and −2.1% respectively whereas for pelvic plans, the biggest discrepancies were −32.7%, −0.4% and -33.5% respectively. The dosimetric impact from hip prosthesis is greater because it produces more artifacts compared to dental fillings. Coverage to PTV can increase or decrease depending on the artifacts since dark streaks reduce the HU whereas bright streaks increase the HU. In the majority of the cases, PTV dose in the non-MAR plans is higher than MAR plans. Conclusion: With the presence of metals, MAR algorithm can allow more accurate delineation of targets and OARs. Dose difference between MAR and non-MAR plans depends on the proximity of the organ to the high density material, the streaking artifacts and the beam arrangements of the plan.

60 APPLIED LIFE SCIENCES↗

An algorithmic calibration approach to identify globally optimal parameters for constraining the DayCent model

he accurate calibration of complex biogeochemical models is essential for the robust estimation of soil greenhouse gases (GHG) as well as other environmental conditions and parameters that are used in research and policy decisions. DayCent is a popular biogeochemical model used both nationally and internationally for this purpose. Despite DayCent’s popularity, its complex parameter estimation is often based on experts’ knowledge which is somewhat subjective. In this study we used the inverse modelling parameter estimation software (PEST), to calibrate the DayCent model based on sensitivity and identifi- ability analysis. Using previously published N2 O and crop yield data as a basis of our calibration approach, we found that half of the 140 parameters used in this study were the primary drivers of calibration dif- ferences (i.e. the most sensitive) and the remaining parameters could not be identified given the data set and parameter ranges we used in this study. The post calibration results showed improvement over the pre-calibration parameter set based on, a decrease in residual differences 79% for N2O fluxes and 84% for crop yield, and an increase in coefficient of determination 63% for N2O fluxes and 72% for corn yield. The results of our study suggest that future studies need to better characterize germination tem- perature, number of degree-days and temperature dependency of plant growth; these processes were highly sensitive and could not be adequately constrained by the data used in our study. Furthermore, the sensitivity and identifiability analysis was helpful in providing deeper insight for important processes and associated parameters that can lead to further improvement in calibration of DayCent model.

Corn yield↗

Multiscale Informatics for Low-Temperature Propane Oxidation: Further Complexities in Studies of Complex Reactions

We have developed a multi-scale approach (Burke, M. P.; Klippenstein, S. J.; Harding, L. B. Proc. Combust. Inst. 2013, 34, 547–555.) to kinetic model formulation that directly incorporates elementary kinetic theories as a means to provide reliable, physics-based extrapolation to unexplored conditions. Here, we extend and generalize the multi-scale modeling strategy to treat systems of considerable complexity – involving multi-well reactions, potentially missing reactions, non-statistical product branching ratios, and non-Boltzmann (i.e. non-thermal) reactant distributions. The methodology is demonstrated here for a subsystem of low-temperature propane oxidation, as a representative system for low-temperature fuel oxidation. A multi-scale model is assembled and informed by a wide variety of targets that include ab initio calculations of molecular properties, rate constant measurements of isolated reactions, and complex systems measurements. Active model parameters are chosen to accommodate both “parametric” and “structural” uncertainties. Theoretical parameters (e.g. barrier heights) are included as active model parameters to account for parametric uncertainties in the theoretical treatment; experimental parameters (e.g. initial temperatures) are included to account for parametric uncertainties in the physical models of the experiments. RMG software is used to assess potential structural uncertainties due to missing reactions. Additionally, branching ratios among product channels are included as active model parameters to account for structural uncertainties related to difficulties in modeling sequences of multiple chemically activated steps. The approach is demonstrated here for interpreting time-resolved measurements of OH, HO2, n-propyl, i-propyl, propene, oxetane, and methyloxirane from photolysis-initiated low-temperature oxidation of propane at pressures from 4 to 60 Torr and temperatures from 300 to 700 K. In particular, the multi-scale informed model provides a consistent quantitative explanation of both ab initio calculations and time-resolved species measurements. The present results show that interpretations of OH measurements are significantly more complicated than previously thought – in addition to barrier heights for key transition states considered previously, OH profiles also depend on additional theoretical parameters for R + O2 reactions, secondary reactions, QOOH + O2 reactions, and treatment of non-Boltzmann reaction sequences. Extraction of physically rigorous information from those measurements may require more sophisticated treatment of all of those model aspects, as well as additional experimental data under more conditions, to discriminate among possible interpretations and ensure model reliability. Keywords: Optimization, Uncertainty quantification, Chemical mechanism, Low-Temperature Oxidation, Non-Boltzmann

Chemical mechanism↗

Influence of Fuel Properties on Gasoline Direct Injection Particulate Matter Emissions Over First 200 s of World-Harmonized Light-Duty Test Procedure Using an Engine Dynamometer and Novel “Virtual Drivetrain” Software

Abstract The influence of fuel properties on particulate matter (PM) emissions from a catalytic gasoline particulate filter (GPF) equipped gasoline direct injection (GDI) engine was investigated using novel “virtual drivetrain” software and an engine mated to an engine dynamometer. The virtual drivetrain software was developed in labview to operate the engine on an engine dynamometer as if it were in a vehicle undergoing a driving cycle. The software uses a physics-based approach to determine vehicle acceleration and speed based on engine load and a programed “shift” schedule to control engine speed. The software uses a control algorithm to modulate engine load and braking to match a calculated vehicle speed with the prescribed speed trace of the driving cycle of choice. The first 200 s of the World-harmonized Light-duty Test Procedure (WLTP) driving cycle was tested using six different fuel formulations of varying volatility, aromaticity, and ethanol concentration. The first 200 s of the WLTP was chosen as the test condition because it is the most problematic section of the driving cycle for controlling PM emissions due to the cold start and cold drive off. It was found that there was a strong correlation between aromaticity of the fuel and the engine-out PM emissions, with the highest emitting fuel producing more than double the mass emissions of the low PM production fuel. However, the post-GPF PM emissions depended greatly on the soot loading state of the GPF. The fuel with the highest engine-out PM emissions produced comparable post-GPF emissions to the lowest PM producing fuel over the driving cycle when the GPF was loaded over three cycles with the respective fuels. These results demonstrate the importance of GPF loading state when aftertreatment systems are used for PM reduction. It also shows that GPF control may be more important than fuel properties, and that regulatory compliance for PM can be achieved with proper GPF control calibration irrespective of fuel type.

Energy & Fuels↗

Requirements Description of GAMSOR and GAMSRC

This report presents the modeling and simulation capabilities of Argonne National Laboratory’s GAMSOR and GAMSRC code that is used in present reactor analysis activities. These capabilities will then be used to establish the set of verification tasks necessary to verify GAMSOR for use on commercial projects. A similar approach was taken for the PERSENT, REBUS and DIF3D software packages. The GAMSOR program is a modified version of DIF3D used to obtain the coupled neutron gamma flux distributions for a given reactor system. GAMSOR was first developed in the 1980s and its work has progressed in parallel with DIF3D throughout its various development phases. While GAMSOR is compatible with DIF3D-FD and DIF3D-Nodal, DIF3D-VARIANT is most commonly used today and will be the focus of the present verification effort. As covered in [1], GAMSOR was built to provide more accurate heating distributions by explicitly solving for both the gamma and neutron heating distributions. Without this consideration, gamma heat is normally assumed to be deposited locally at the site of gamma production. This is acceptable for modeling some phenomena because the total energy production is preserved, but it can lead to inaccurate approximations of fluence-dependent behaviors such as fuel performance, swelling, cladding embrittlement, radiation induced creep, and power peaking. The outputs from GAMSOR are contained in multiple intermediate and final output files: FIXSRC, VARSRC, GTFLUX, GHFLUX, PWDINT, NPDINT, and GPDINT. DIF3D normally produces a PWDINT file containing power density results, with the assumption that gamma rays are absorbed where they are emitted (i.e., energy deposition is local with no modeled transport). With GAMSOR, neutron power density (NPDINT) and gamma power density (GPDINT) are both produced, with their summed power densities replacing the results in PWDINT for total heating (i.e., recoverable) power density.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SU-E-T-455: Impact of Different Independent Dose Verification Software Programs for Secondary Check

Purpose: There have been many reports for different dose calculation algorithms for treatment planning system (TPS). Independent dose verification program (IndpPro) is essential to verify clinical plans from the TPS. However, the accuracy of different independent dose verification programs was not evident. We conducted a multi-institutional study to reveal the impact of different IndpPros using different TPSs. Methods: Three institutes participated in this study. They used two different IndpPros (RADCALC and Simple MU Analysis (SMU), which implemented the Clarkson algorithm. RADCALC needed the input of radiological path length (RPL) computed by the TPSs (Eclipse or Pinnacle3). SMU used CT images to compute the RPL independently from TPS). An ion-chamber measurement in water-equivalent phantom was performed to evaluate the accuracy of two IndpPros and the TPS in each institute. Next, the accuracy of dose calculation using the two IndpPros compared to TPS was assessed in clinical plan. Results: The accuracy of IndpPros and the TPSs in the homogenous phantom was +/−1% variation to the measurement. 1543 treatment fields were collected from the patients treated in the institutes. The RADCALC showed better accuracy (0.9 ± 2.2 %) than the SMU (1.7 ± 2.1 %). However, the accuracy was dependent on the TPS (Eclipse: 0.5%, Pinnacle3: 1.0%). The accuracy of RADCALC with Eclipse was similar to that of SMU in one of the institute. Conclusion: Depending on independent dose verification program, the accuracy shows systematic dose accuracy variation even though the measurement comparison showed a similar variation. The variation was affected by radiological path length calculation. IndpPro with Pinnacle3 has different variation because Pinnacle3 computed the RPL using physical density. Eclipse and SMU uses electron density, though.

60 APPLIED LIFE SCIENCES↗

The effect of open-cell metal foams strut shape on convection heat transfer and pressure drop

Metal foams are promising materials for applications where enhancement of heat transfer is needed. Their performance depends on morphological parameters, such as the diameters of cells, pores, and struts, the porosity, the shape of struts. The effect of strut shape on convection heat transfer and pressure drop in open-cell metal foams has been investigated numerically in this paper by introducing the foam shape factor, a parameter that characterizes the shape of the strut. The analysis has been carried out both on real and ideal foams. The geometry of three 40 Pores Per Inch (PPI) real foams, with 0.87, 0.94 and 0.96 average measured porosities, was determined with X-ray Computed Microtomography (XCT) and a morphological analysis of the XCT data was carried out. The geometry of the ideal foams, based on the Lord Kelvin foam model, with the same PPI and porosities as those of the real foams, was generated with the free-to-use software Surface Evolver, building up foams with different strut shapes. Governing equations have been solved with a finite element scheme, assuming a uniform heat flux condition at the solid/fluid boundary of the foam. Results are presented in terms of convection heat transfer coefficients and pressure distributions as a function of strut shape parameters. Here, the comparison between predictions for ideal and real foams, for different strut shapes, confirms that, in all cases, the closer the form of the ideal strut to that of the real strut the better the agreement among predictions. It is also pointed out that the convection heat transfer coefficient is maximized when, at equal porosity, the ligament shape is convex, while a concave strut shape maximizes the pressure drop.

42 ENGINEERING↗

High-order, linearly stable, partitioned solvers for general multiphysics problems based on implicit–explicit Runge–Kutta schemes

This work introduces a general framework for constructing high-order, linearly stable, partitioned solvers for multiphysics problems from a monolithic implicit–explicit Runge–Kutta (IMEX-RK) discretization of the semi-discrete equations. The generic multiphysics problem is modeled as a system of n systems of partial differential equations where the i th subsystem is coupled to the other subsystems through a coupling term that can depend on the state of all the other subsystems. This coupled system of partial differential equations reduces to a coupled system of ordinary differential equations via the method of lines where an appropriate spatial discretization is applied to each subsystem. The coupled system of ordinary differential equations is taken as a monolithic system and discretized using an IMEX-RK discretization with a specific implicit–explicit decomposition that introduces the concept of a predictor for the coupling term. We propose four coupling predictors that enable the monolithic system to be solved in a partitioned manner, i.e., subsystem-by-subsystem, and preserve the IMEX-RK structure and therefore the design order of accuracy of the monolithic scheme. The four partitioned solvers that result from these predictors are high-order accurate, allow for maximum re-use of existing single-physics software, and two of the four solvers allow the subsystems to be solved in parallel at a given stage and time step. We also analyze the stability of a coupled, linear model problem with a specific coupling structure and show that one of the partitioned solvers achieves unconditional linear stability for this problem, while the others are unconditionally stable only for certain values of the coupling strength. We demonstrate the performance of the proposed partitioned solvers on several classes of multiphysics problems including a simple linear system of ODEs, advection–diffusion–reaction systems, fluid–structure interaction problems, and particle-laden flows, where we verify the design order of the IMEX schemes and study various stability properties.

97 MATHEMATICS AND COMPUTING↗

LCOE reduction through proactively optimized monitoring of PV Systems (Final Technical Report)

The project demonstrates the value proposition for a high-resolution monitoring system (HRMS) with diagnostic-prognostic capability and determine its impact on LCOE. The HRMS differs from conventional monitoring systems in a number of ways. First it will include the capability to automatically measure IV curves at the string and module levels. This provides a much richer view into the DC performance of the PV system and allows classification of many typical failure and degradation modes. Second, it will incorporate software capable of quantifying power and energy losses in the field as well as define the location and mechanism of the power and energy loss. Moreover, we aimed to deliver a prognostic system that is capable of predicting certain failures before they occur and giving system operators the opportunity to more efficiently plan operations and maintenance (O&M) activity in order to lower costs and increase yield over the life of the system. The research identifies cost targets required for different monitoring stages, including at the string combiner, at the individual string, and at the module level, to lower the levelized cost of energy (LCOE). Finally, a comprehensive guide determines the value PV monitoring brings to PV field operations. The guide assists plant operators in maximizing value from existing plants and identify the trade-offs of different monitoring solutions for future plants depending on the size, location, and expected system lifetime.

14 SOLAR ENERGY↗

A Monte Carlo model for 3D grain evolution during welding

Welding is one of the most wide-spread processes used in metal joining. However, there are currently no open-source software implementations for the simulation of microstructural evolution during a weld pass. Here we describe a Potts Monte Carlo based model implemented in the SPPARKS kinetic Monte Carlo computational framework. The model simulates melting, solidification and solid-state microstructural evolution of material in the fusion and heat-affected zones of a weld. The model does not simulate thermal behavior, but rather utilizes user input parameters to specify weld pool and heat-affect zone properties. Weld pool shapes are specified by Bezier curves, which allow for the specification of a wide range of pool shapes. Pool shapes can range from narrow and deep to wide and shallow representing different fluid flow conditions within the pool. Surrounding temperature gradients are calculated with the aide of a closest point projection algorithm. Furthermore, the model also allows simulation of pulsed power welding through time-dependent variation of the weld pool size. Example simulation results and comparisons with laboratory weld observations demonstrate microstructural variation with weld speed, pool shape, and pulsed-power.

36 MATERIALS SCIENCE↗

Final Technical Report: Amicus O&M Cooperative

Despite the maturation of the broader solar PV industry, the operations and maintenance (O&M) market segment is still relatively under developed. The lack of industry coherence jeopardizes the long-term performance of multiple gigawatts of installed capacity, and thus, the legitimacy of solar PV as a dependable source of electricity generation in the U.S. To address these challenges, the project team formed a new company, the Amicus Operations and Maintenance (O&M) Cooperative, whose mission is to ensure that solar PV fulfills its promise as a responsible and reliable energy source, for generations to come. Amicus O&M Cooperative created solutions to the market gaps by establishing a consistent level of O&M service offerings; standardizing scopes of work and legal agreements; training and certifying technicians; minimizing transaction costs for asset owners; and mitigating risk by creating redundancy in the companies who are able to perform work to these standards. We attracted double the number of member-companies originally forecast (goal: 10, actual: 20), broadening the reach of the service area, minimizing travel costs, and reducing response times for O&M services. We built a professional website and a software platform for managing work orders. Lastly, we have established multiple channels for communication among members, including monthly calls for sales topics and for technical/operational topics, an intranet for announcements/ questions/articles, and regular in-person meetings in association with the meetings of our sister cooperative, Amicus Solar. Throughout the project, participants sought feedback, input, and insights from stakeholders in the O&M market segment, including current and potential member-companies and potential clients. The problem statement above was confirmed many times over, with additional insight on the need for more workforce development, driving efficiency and lowering cost through better data analysis and remote diagnostics, and finding ways to reduce the cost of secondary and ancillary services as well (including items such as vegetation management and module cleaning). For solar to maintain its status as a reliable energy source – and for it to continue attracting investment – it must perform to expectation. This is where solar PV O&M technicians come into play. The cooperative helps them perform their work more cost effectively by streamlining “soft costs” including legal costs and work management, as well as reducing travel time and expenses. The new cooperative has demonstrated significant price reductions for O&M services relative to reported industry averages, which benefits clients directly and the public indirectly through cleaner air, economic development, and job growth.

14 SOLAR ENERGY↗

On Eliminating Synchronous Communication in Molecular Simulations to Improve Scalability

Molecular dynamics simulation, as a complementary tool to experimentation, has become an important methodology for the understanding and design of molecular systems as it provides access to properties that are difficult, impossible or prohibitively expensive to obtain experimentally. Many of the available software packages have been parallelized to take advantage of modern massively concurrent processing resources. The challenge in achieving parallel efficiency is commonly attributed to the fact that molecular dynamics algorithms are communication intensive. This paper illustrates how an appropriately chosen data distribution and asynchronous one-sided communication approach can be used to effectively deal with the data movement within the Global Arrays/ARMCI programming model framework. A new put_notify capability is presented here, allowing the implementation of the molecular dynamics algorithm without any explicit global or local synchronization or global data reduction operations. In addition, this push-data model is shown to very effectively allow hiding data communication behind computation. Rather than data movement or explicit global reductions, the implicit synchronization of the algorithm becomes the primary challenge for scalability. Without any explicit synchronous operations, the scalability of molecular simulations is shown to depend only on the ability to evenly balance computational load.

Straatsma, TP↗

3D Optical Coherence Tomography image processing in BISCAP: characterization of biofilm structure and properties

Abstract Motivation BISCAP is a state-of-the-art tool for automatically characterizing biofilm images obtained from Optical Coherence Tomography. Limited availability of other software tools is reported in the field. BISCAP’s first version processes 2D images only. Processing 3D images is a problem of greater scientific relevance since it deals with the entire structure of biofilms instead of their 2D slices. Results Building on the image-processing principles and algorithms proposed earlier for 2D images, these were adapted to the 3D case, and a more general implementation of BISCAP was developed. The primary goal concerns the extension of the initial methodology to incorporate the depth axis in 3D images; multiple improvements were also made to boost computational performance. The calculation of structural properties and visual outputs was extended to offer new insights into the 3D structure of biofilms. BISCAP was tested using 3D images of biofilms with different morphologies, consistently delivering accurate characterizations of 3D structures in a few minutes using standard laptop machines. Low user dependency is required for image analysis. Availability and implementation BISCAP is available from https://github.com/diogonarciso/BISCAP. All images used in the tutorials and the validation examples are available from https://web.fe.up.pt/∼fgm/biscap3d.

Narciso, Diogo A. C. (ORCID:0000000227767477)↗

Parametric analysis on optimized design of hybrid solar power plants

There is increasing interest in utility-scale solar power plants with storage which can flexibly dispatch renewable energy to the grid. However, plant design possesses many degrees of freedom and non-obvious trade-offs in performance. Software tools can estimate or optimize the performance of a specific plant configuration under market and weather conditions of interest; the associated cost parameters and operating assumptions strongly influence estimates of plant performance and decisions regarding optimal sizing. We employ the National Renewable Energy Laboratory's Hybrid Optimization and Performance Platform, which incorporates optimal dispatch when evaluating plant performance, and investigate the sensitivity to weather and market conditions, operating limitations, and the presence of a capacity-based incentive. We demonstrate changes in plant performance and optimal sizing with respect to these inputs and discuss implications. Here results show that PV-with-battery designs are more profitable under our assumptions, but that designs including a concentrated solar power (CSP) system produce significantly greater annual energy; and that CSP-with-thermal energy storage designs maximizing the benefit-to-cost ratio have an input-dependent linear relationship between the CSP field solar multiple and the hours of storage as the project budget varies.

14 SOLAR ENERGY↗

Toward General Software Level Silent Data Corruption Detection for Parallel Applications

Silent data corruption (SDC) poses a great challenge for high-performance computing (HPC) applications as we move to extreme-scale systems. Mechanisms have been proposed that are able to detect SDC in HPC applications by using the peculiarities of the data (more specifically, its “smoothness” in time and space) to make predictions. However, these data-analytic solutions are still far from fully protecting applications to a level comparable with more expensive solutions such as full replication. In this work, we propose partial replication to overcome this limitation. More specifically, we have observed that not all processes of an MPI application experience the same level of data variability at exactly the same time. Thus, we can smartly choose and replicate only those processes for which the lightweight data-analytic detectors would perform poorly. In addition, we propose a new evaluation method based on the probability that a corruption will pass unnoticed by a particular detector (instead of just reporting overall single-bit precision and recall). Here in our experiments, we use four applications dealing with different explosions. Finally, our results indicate that our new approach can protect the MPI applications analyzed with 7–70% less overhead (depending on the application) than that of full duplication with similar detection recall.

97 MATHEMATICS AND COMPUTING↗

A robust return-map algorithm for general multisurface plasticity

Three new contributions to the field of multisurface plasticity are presented for general situations with an arbitrary number of nonlinear yield surfaces with hardening or softening. A method for handling linearly dependent flow directions is described. A residual that can be used in a line search is defined. An algorithm that has been implemented and comprehensively tested is discussed in detail. Examples are presented to illustrate the computational cost of various components of the algorithm. The overall result is that a single Newton-Raphson iteration of the algorithm costs between 1.5 and 2 times that of an elastic calculation. Examples also illustrate the successful convergence of the algorithm in complicated situations. For example, without using the new contributions presented here, the algorithm fails to converge for approximately 50% of the trial stresses for a common geomechanical model of sedementary rocks, while the current algorithm results in complete success. Since it involves no approximations, the algorithm is used to quantify the accuracy of an efficient, pragmatic, but approximate, algorithm used for sedimentary-rock plasticity in a commercial software package. Furthermore, the main weakness of the algorithm is identified as the difficulty of correctly choosing the set of initially active constraints in the general setting.

15 GEOTHERMAL ENERGY↗