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DOE OSTI2016

Software development infrastructure for the HYBRID modeling and simulation project

One of the goals of the HYBRID modeling and simulation project is to assess the economic viability of hybrid systems in a market that contains renewable energy sources like wind. The idea is that it is possible for the nuclear plant to sell non-electric energy cushions, which absorb (at least partially) the volatility introduced by the renewable energy sources. This system is currently modeled in the Modelica programming language. To assess the economics of the system, an optimization procedure is trying to find the minimal cost of electricity production. The RAVEN code is used as a driver for the whole problem. It is assumed that at this stage, the HYBRID modeling and simulation framework can be classified as non-safety “research and development” software. The associated quality level is Quality Level 3 software. This imposes low requirements on quality control, testing and documentation. The quality level could change as the application development continues.Despite the low quality requirement level, a workflow for the HYBRID developers has been defined that include a coding standard and some documentation and testing requirements. The repository performs automated unit testing of contributed models. The automated testing is achieved via an open-source python script called BuildingsP from Lawrence Berkeley National Lab. BuildingsPy runs Modelica simulation tests using Dymola in an automated manner and generates and runs unit tests from Modelica scripts written by developers. In order to assure effective communication between the different national laboratories a biweekly videoconference has been set-up, where developers can report their progress and issues. In addition, periodic face-face meetings are organized intended to discuss high-level strategy decisions with management. A second means of communication is the developer email list. This is a list to which everybody can send emails that will be received by the collective of the developers and managers involved in the project. Thirdly, to exchange documents quickly, a SharePoint directory has been set-up. SharePoint allows teams and organizations to intelligently share, and collaborate on content from anywhere.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

CSP ELEMENTS: High-Temperature Thermochemical Storage with Redox-Stable Perovskites for Concentrating Solar Power

This project was motivated by the potential of reducible perovskite oxides for high-temperature, thermochemical energy storage (TCES) to provide dispatchable renewable heat for concentrating solar power (CSP) plants. This project sought to identify and characterize perovskites from earth-abundant cations with high reducibility below 1000 °C for coupling TCES of solar energy to super-critical CO2 (s-CO2) plants that operate above temperature limits (< 600 °C) of current molten-salt storage. Specific TCES > 750 kJ/kg for storage cycles between 500 and 900 °C was targeted with a system cost goal of $15/kWhth. To realize feasibility of TCES systems based on reducible perovskites, our team focused on designing and testing a lab-scale concentrating solar receiver, wherein perovskite particles capture solar energy by fast O2 release and sensible heating at a thermal efficiency of 90% and wall temperatures below 1100 °C. System-level models of the receiver and reoxidation reactor coupled to validated thermochemical materials models can assess approaches to scale-up a full TCES system based on reduction/oxidation cycles of perovskite oxides at large scales. After characterizing many Ca-based perovskites for TCES, our team identified strontium-doped calcium manganite Ca1-xSrxMnO3-δ (with x ≤ 0.1) as a composition with adequate stability and specific TCES capacity (> 750 kJ/kg for Ca0.95Sr0.05MnO3-δ) for cycling between air at 500 °C and low-PO2 (10-4 bar) N2 at 900 °C. Substantial kinetic tests demonstrated that resident times of several minutes in low-PO2 gas were needed for these materials to reach the specific TCES goals with particles of reasonable size for large-scale transport (diameter dp > 200 μm). On the other hand, fast reoxidation kinetics in air enables subsequent rapid heat release in a fluidized reoxidation reactor/ heat recovery unit for driving s-CO2 power plants. Validated material thermochemistry coupled to radiation and convective particle-gas transport models facilitated full TCES system analysis for CSP and results showed that receiver efficiencies approaching 85% were feasible with wall-to-particle heat transfer coefficients observed in laboratory experiments. Coupling these reactive particle-gas transport models to external SolTrace and CFD models drove design of a reactive-particle receiver with indirect heating through flux spreading. A lab-scale receiver using Ca0.9Sr0.1MnO3-δ was demonstrated at NREL’s High Flux Solar Furnace with particle temperatures reaching 900 °C while wall temperatures remained below 1100 °C and approximately 200 kJ/kg of chemical energy storage. These first demonstrations of on-sun perovskite reduction and the robust modeling tools from this program provide a basis for going forward with improved receiver designs to increase heat fluxes and solar-energy capture efficiencies. Measurements and modeling tools from this project provide the foundations for advancing TCES for CSP and other applications using reducible perovskite oxides from low-cost, earth-abundant elements. A perovskite composition has been identified that has the thermodynamic potential to meet the targeted TCES capacity of 750 kJ/kg over a range of temperatures amenable for integration with s-CO2 cycles. Further research needs to explore ways of accelerating effective particle kinetics through variations in composition and/or reactor/receiver design. Initial demonstrations of on-sun particle reduction for TCES show a need for testing at larger scales with reduced heat losses and improved particle-wall heat transfer. The gained insight into particle-gas transport and reactor design can launch future development of cost-effective, large-scale particle-based TCES as a technology for enabling increased renewable energy penetration.

14 SOLAR ENERGY↗

DOE OSTI2021

VERA-Grizzly Ex-Core Calculations: Watts Bar Unit 1 Cycles 1-2

The critical structures that comprise light-water reactor (LWR) nuclear power plants are subjected to operating environments that can challenge their integrity. Structures in close proximity to the reactor core, such as the reactor pressure vessel (RPV) and the biological shield wall, are subjected to high levels of radiation emanating from the core, as well as elevated temperatures. As the US fleet of operating LWRs ages, the effects of these operating environments on the integrity of these structures must be considered to ensure their continued safe operation. Extending the lifetime of commercial reactors and maintaining the aging reactor fleet require accurate prediction of the exposure of ex-core components to neutron and photon radiation. In particular, concrete degradation studies must be performed to evaluate the safety and long-term operation of reactors with lifetime extensions. The concrete reactor bioshield is important for providing radiological protection during operation and must last for the entire lifetime of the reactor. Recent interest in lifetime extensions furthers the need to accurately simulate concrete material degradation in the reactor bioshield. As a result of this need, the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has funded this study to couple its tools, Virtual Environment for Reactor Applications (VERA) and Grizzly. VERA allows users to set up models to calculate time-dependent and fully coupled solutions (with thermal feedback) for ex-core quantities of interest such as vessel and coupon fluence and detector responses for multiple statepoints and cycles. Grizzly is a finite-element application based on the Multiphysics Object Oriented Simulation Environment (MOOSE) framework that is used to enable aging materials calculations. This report highlights the work performed to calculate the fluence in the vessel and concrete for Watts Bar Nuclear Plant Unit 1 (WBN1) Cycles 1 and 2. The fluences obtained from VERA were successfully transferred to Grizzly using a Python script. Four simulations were run with Grizzly: (1) the Mazars model with the initial Young’s modulus being the instantaneous modulus, (2) the Mazars model with the initial Young’s modulus being the delayed modulus, (3) the Mazars model with the initial Young’s modulus being the delayed modulus with the addition of the effects of micro-damage caused by irradiation, and (4) the Mazars model with the initial Young’s modulus being the instantaneous modulus, and with the addition of micro-damage and creep. Details regarding the methods used to obtain the fluence and the statistical errors associated with the VERA Monte Carlo Shift calculations are discussed in greater detail in this report. The results obtained from the four Grizzly models are also presented in this report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2017

Robust planning of dynamic wireless charging infrastructure for battery electric buses

Battery electric buses with zero tailpipe emissions have great potential in improving environmental sustainability and livability of urban areas. However, the problems of high cost and limited range associated with on-board batteries have substantially limited the popularity of battery electric buses. The technology of dynamic wireless power transfer (DWPT), which provides bus operators with the ability to charge buses while in motion, may be able to effectively alleviate the drawbacks of electric buses. In this paper, we address the problem of simultaneously selecting the optimal location of the DWPT facilities and designing the optimal battery sizes of electric buses for a DWPT electric bus system. The problem is first constructed as a deterministic model in which the uncertainty of energy consumption and travel time of electric buses is neglected. The methodology of robust optimization (RO) is then adopted to address the uncertainty of energy consumption and travel time. The affinely adjustable robust counterpart (AARC) of the deterministic model is developed, and its equivalent tractable mathematical programming is derived. Both the deterministic model and the robust model are demonstrated with a real-world bus system. The results of our study demonstrate that the proposed deterministic model can effectively determine the allocation of DWPT facilities and the battery sizes of electric buses for a DWPT electric bus system; and the robust model can further provide optimal designs that are robust against the uncertainty of energy consumption and travel time for electric buses.

25 ENERGY STORAGE↗

DOE OSTI2023

Cycle-by-cycle Delay Estimation at Signalized Intersections by using Machine Learning and Simulated Video Detection Data

Accurate estimation of delay is crucial for efficient traffic signal operations. Estimation of delay in the real-time manner using traditional loop detectors requires advanced detectors (in addition to stop-bar detection). In cases when this detection layout is not in place, delay estimates are approximated with a lower accuracy. Video detection is one of the most frequently deployed detection systems at signalized intersections in recent years. In most cases video detection operates in the same way as traditional inductive loops. However, when coupled with computer vision algorithms, video detection systems could be used to retrieve additional information (e.g., vehicular arrivals and departures) that cannot be taken out from the conventional systems (e.g., long stop-bar loop detectors). Although present for several decades, video detection data were not frequently examined for delay estimation purposes. In this study, we proposed a novel delay estimation model which can be developed with only data from stop-bar video detectors. Relevant data were collected from a simulation model of 11 signalized intersections at downtown Chattanooga, TN and processed to create needed inputs for model development. With the use of multigene genetic programming the authors developed a delay model that outperforms accuracy of multi regression model. Furthermore, authors evaluated the developed model by comparison with the other benchmark delay models, such as HCM and approach delay model. It was found that the developed MGGP delay model outperforms benchmark models for a wide range of traffic and signal operation conditions.

Erdagi, Ismet Goksad↗

DOE OSTI2021

Ionizing radiation effects in SONOS-based neuromorphic inference accelerators

Here, we evaluate the sensitivity of neuromorphic inference accelerators based on Silicon-Oxide-Nitride-Oxide-Silicon (SONOS) charge trap memory arrays to total ionizing dose (TID) effects. Data retention statistics were collected for 16 Mbit of 40 nm SONOS digital memory exposed to ionizing radiation from a Co-60 source, showing good retention of the bits up to the maximum dose of 500 krad(Si). Using this data, we formulate a rate-equation-based model for the TID response of trapped charge carriers in the ONO stack, and predict the effect of TID on intermediate device states between ‘program’ and ‘erase’. This model is then used to simulate arrays of low-power, analog SONOS devices that store 8-bit neural network weights and support in situ matrix-vector multiplication. We evaluate the accuracy of the irradiated SONOS-based inference accelerator on two image recognition tasks – CIFAR-10 and the challenging ImageNet dataset – using state-of-the-art convolutional neural networks, such as ResNet-50. We find that across the datasets and neural networks evaluated, the accelerator tolerates a maximum TID between 10 krad(Si) and 100 krad(Si), with deeper networks being more susceptible to accuracy losses due to TID.

43 PARTICLE ACCELERATORS↗

DOE OSTI2015

Replacement of tritiated water from irradiated fuel storage bay

Recently, AECL developed a novel method to reduce tritium emissions (to groundwater) and personnel doses at the NRU (National Research Universal) reactor irradiated fuel storage bay (also known as rod or spent fuel bay) through a water swap process. The light water in the fuel bay had built up tritium that had been transferred from the heavy water moderator through normal fuel transfers. The major advantage of the thermal stratification method was that a very effective tritium reduction could be achieved by swapping a minimal volume of bay water and warm tritiated water would be skimmed off the bay surface. A demonstration of the method was done that involved Computational Fluid Dynamics (CFD) modeling of the swap process and a test program that showed excellent agreement with model prediction for the effective removal of almost all the tritium with a minimal water volume. Building on the successful demonstration, AECL fabricated, installed, commissioned and operated a full-scale system to perform a water swap. This full-scale water swap operation achieved a tritium removal efficiency of about 96%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2017

Systems Engineering Model for ART Energy Conversion

The near-term objective of the EC team is to establish an operating, commercially scalable Recompression Closed Brayton Cycle (RCBC) to be constructed for the NE - STEP demonstration system (demo) with the lowest risk possible. A systems engineering approach is recommended to ensure adequate requirements gathering, documentation, and mode ling that supports technology development relevant to advanced reactors while supporting crosscut interests in potential applications. A holistic systems engineering model was designed for the ART Energy Conversion program by leveraging Concurrent Engineering, Balance Model, Simplified V Model, and Project Management principles. The resulting model supports the identification and validation of lifecycle Brayton systems requirements, and allows designers to detail system-specific components relevant to the current stage in the lifecycle, while maintaining a holistic view of all system elements.

42 ENGINEERING↗

DOE OSTI2017

2017 GTO Project review Laboratory Evaluation of EGS Shear Stimulation.

The objectives and purpose of this research has been to produce laboratory-based experimental and numerical analyses to provide a physics-based understanding of shear stimulation phenomena (hydroshearing) and its evolution during stimulation. Water was flowed along fractures in hot and stressed fractured rock, to promote slip. The controlled laboratory experiments provide a high resolution/high quality data resource for evaluation of analysis methods developed by DOE to assess EGS “behavior” during this stimulation process. Segments of the experimental program will provide data sets for model input parameters, i.e., material properties, and other segments of the experimental program will represent small scale physical models of an EGS system, which may be modeled. The coupled lab/analysis project has been a study of the response of a fracture in hot, water-saturated fractured rock to shear stress experiencing fluid flow. Under this condition, the fracture experiences a combination of potential pore pressure changes and fracture surface cooling, resulting in slip along the fracture. The laboratory work provides a means to assess the role of “hydroshearing” on permeability enhancement in reservoir stimulation. Using the laboratory experiments and results to define boundary and input/output conditions of pore pressure, thermal stress, fracture shear deformation and fluid flow, and models were developed and simulations completed by the University of Oklahoma team. The analysis methods are ones used on field scale problems. The sophisticated numerical models developed contain parameters present in the field. The analysis results provide insight into the role of fracture slip on permeability enhancement-“hydroshear” is to be obtained. The work will provide valuable input data to evaluate stimulation models, thus helping design effective EGS.

58 GEOSCIENCES↗

DOE OSTI2019

Low-Loss, High-Flux Saturation Magnetic Cores for Power Converters

As new and alternative energy sources are added to the energy grid, efficient and low-loss power converters are essential to the storage of energy from these intermittent power sources. Higher operating frequency can reduce the size and weight of transformers. However, current magnetic cores limit the operating frequency because core losses increase with frequency. Therefore, new magnetic core materials are needed with higher resistivity (lower eddy-current losses), lower coercivity (lower hysteresis losses), and higher permeability and flux density (higher power density). These new materials must be integrated into isolated power converters designed to optimize efficiency based on the transformer performance. To address this need, Mainstream pursued a two-pronged approach in Phase I to develop novel magnetic materials and model a planar transformer design. We irradiated silicon steel with a high-energy electron beam in an attempt to induce nanocrystalline grain formation. The nanocrystalline grains were expected to increase resistivity to reduce eddy-current losses and decrease coercivity to reduce hysteresis losses. We also modeled the transformer performance through Simulation Program with Integrated Circuit Emphasis (SPICE) and analytical models to establish the effect of magnetic properties of the core on the performance of the transformer. There still are hurdles to be overcome in Phase II. The electron beam processing was successful in increasing the resistivity and the flux saturation density. However, the resistivity is still too low for high-frequency magnetic cores, because the eddy-current losses would be prohibitively high. Additionally, the coercivity increased for the processed samples leading to higher hysteresis losses. In comparing our SPICE and analytical models to the planar transformer measured values and impedance plots, good agreement was seen for primary and secondary short-circuit impedance measurements and for primary-to-secondary capacitance measurements. The SPICE model deviated from measured values, though, when measuring the transformer open-circuit impedance, indicating that we might need to add more model complexity to the transformer model. Phase II research will continue to build on the transformer model and integrating novel magnetic materials into high-frequency transformers.

15 GEOTHERMAL ENERGY↗

DOE OSTI2019

HOMMEXX 1.0: a performance-portable atmospheric dynamical core for the Energy Exascale Earth System Model

Abstract. We present an architecture-portable and performant implementation of the atmospheric dynamical core (High-Order Methods Modeling Environment, HOMME) of the Energy Exascale Earth System Model (E3SM). The original Fortran implementation is highly performant and scalable on conventional architectures using the Message Passing Interface(MPI) and Open MultiProcessor (OpenMP) programming models.We rewrite the model in C++ and use the Kokkos library to express on-node parallelism in a largely architecture-independent implementation. Kokkos provides an abstraction of a compute node or device,layout-polymorphic multidimensional arrays, and parallel execution constructs. The new implementation achieves the same or better performance on conventional multicore computers and is portable to GPUs. We present performance data for the original and new implementations on multiple platforms, on up to 5400 compute nodes, and study several aspects of the single- and multi-node performance characteristics of the new implementation on conventional CPU (e.g., Intel Xeon), many core CPU (e.g., Intel Xeon Phi Knights Landing),and Nvidia V100 GPU.

58 GEOSCIENCES↗

DOE OSTI2015

End-to-end interoperability and workflows from building architecture design to one or more simulations

An end-to-end interoperability and workflows from building architecture design to one or more simulations, in one aspect, may comprise establishing a BIM enablement platform architecture. A data model defines data entities and entity relationships for enabling the interoperability and workflows. A data definition language may be implemented that defines and creates a table schema of a database associated with the data model. Data management services and/or application programming interfaces may be implemented for interacting with the data model. Web services may also be provided for interacting with the data model via the Web. A user interface may be implemented that communicates with users and uses the BIM enablement platform architecture, the data model, the data definition language, data management services and application programming interfaces to provide functions to the users to perform work related to building information management.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

End-to-end interoperability and workflows from building architecture design to one or more simulations

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Overview of the U.S. DOE advanced fuels campaign

Advanced Fuel Campaign (AFC) has responsibility to develop advanced nuclear fuel technologies for the Fuel Cycle Research and Development (FCRD) program. AFC focus areas include 4 topics: advanced LWR fuels, actinide transmutation, research infrastructure development for the study of new nuclear fuels and advanced modeling and simulation. This paper reviews the latest technical advances in the 4 topics. Fuel and cladding materials under investigation include the following general classes of technologies: iron-based cladding, ceramic cladding, coated Zirconium alloy cladding, molybdenum-based cladding, high-density fuel, fully ceramic matrix fuel, and metallic alloy-based nuclear fuel. Concerning actinide transmutation fuel alloy additions to immobilize the lanthanide fission products, sodium-free annular fuel concepts, and cladding coatings and liners for mitigation of fuel-cladding chemical interaction have been investigated. Direct casting of metallic fuel into a zirconium liner was demonstrated. A Talos Transmission Electron Microscope was acquired for the study of advanced nuclear fuels and materials. The conceptual and preliminary designs for a static capsule, a flowing water loop, and a flowing sodium loop to support future transient testing needs have been completed. AFC interfaces with the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to develop multi-scale, multi-physics fuel performance codes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Dynamic Modeling of Full Converter Adjustable-speed Pumped Storage Hydropower (FC AS-PSH)

Full converter adjustable-speed pumped storage hydropower (FC AS-PSH) technology, as one of advanced-PSH technology, is developed from wind turbine technology. By making the synchronous machine connect to the grid through a full-size converter, FC AS-PSH has a wider adjustment range of speed and a better reactive power control capability compared with a doubly-fed asynchronous generator AS-PSH technology. When it plays as an energy backup in the power system, FC AS-PSH can provide a much faster response than conventional-PSH (C-PSH) which makes this technology provide better ancillary service for a high renewable penetrated system. In this paper, the dynamic modeling of FC AS-PSH is fully studied. We develop a detailed model of this technology in the IEEE 14-bus system based on GE Positive Sequence Load Flow (PSLF) platform. Especially, the first governor model is developed based on the Engineer’s Program Control Language (EPCL) user-defined model in this platform. All operation modes are validated and studied under a system contingency. Besides, comparison cases between FC AS-PSH and C-PSH are studied to show advantages providing from FC AS-PSH when it works with renewable energy.

50 EE - Wind and Water Power Program - Water (EE-4↗

DOE OSTI2017

Projected precipitation changes within the Great Lakes and Western Lake Erie Basin: a multi‐model analysis of intensity and seasonality

ABSTRACT The Great Lakes region encompasses the largest freshwater lake network in the world and supports a diverse network of agriculture, transportation, and tourism. Recently, Lake Erie has experienced increased hypoxia events, which have been attributed to agricultural practices and changes in run‐off. Here we examine the projected changes in extreme precipitation events to address concerns regarding regional agriculture, surface run‐off, and subsequent water quality. Precipitation projections within the overall Great Lakes Basin and the Western Lake Erie Basin subregion are examined using climate model simulations of varying spatial resolutions to understand historical precipitation and projected future precipitation. We develop three model ensembles for the historical period (1980–1999) and the mid‐century (2041–2060) that cover a range of spatial resolutions and future emissions scenarios, including: (1) 12 global model members from the fifth Climate Model Intercomparison Project ( CMIP5 ) using Representative Concentration Pathway ( RCP ) 8.5, (2) ten regional climate model ( RCM ) members from the North American Regional Climate Change Assessment Program driven by CMIP3 global models using the A2 emissions scenario, and (3) two high resolution RCM simulations ( RCM4 ) driven by CMIP5 global models using the RCP 8.5 scenario. For the historical period, all model ensembles overestimate winter and spring precipitation, and many of the models simulate a summer drying that is not observed. At mid‐century, most of the models predict a 10–20% increase in precipitation depending on the time of year. Daily probability distribution functions from three model ensembles reveal spring seasonal increases in high precipitation event probabilities when compared to the historical period, suggesting an increase in the frequency of high intensity precipitation at mid‐century. Overall, the presence of lakes or higher spatial resolution does not ensure improved representation of historical processes, and more complex interactions between large‐scale dynamics, local feedbacks, and physical parameterizations drive the model spread.

Basile, Samantha J.↗

DOE OSTI2026

or-topas: Operations Research Toolkit for Pyomo Alternative Solutions

SAND2026-16702O OR-TOPAS: Operations Research Toolkit for Pyomo Alternative Solutions is a tool that enhances optimization applications defined by the Pyomo modeling library. It offers functions to generate optimal or near-optimal solutions, operating independently of Pyomo’s solver interface. Users can configure these functions with specific solver names and options, resulting in a custom solution object that returns a list of solutions. The OR-TOPAS library includes methods tailored to the properties of the model, such as binary integer programs versus linear programs, and specific solver interfaces like Gurobi. It does not provide models for specific applications, but it is applicable to a wide range of Pyomo optimization models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Siirola, John [Sandia National Lab. (SNL-CA), Live↗

DOE OSTI2019

Model of temperature, evaporation, and productivity in elevated experimental algae raceways and comparison with commercial raceways

Elevated Experimental Raceways (EERs) have been used at many research sites in the United States to evaluate algal biomass productivity. This paper develops temperature and evaporation models for EERs and then evaluates whether the temperature profile and resultant productivity in an EER is representative of large-scale commercial raceways. Open water surface evaporation and temperature models with shading algorithms were programmed in Python and calibrated with temperature and evaporation data from the EERs in the Regional Algal Feedstock Testbed (RAFT) experiments at the University of Arizona. The final calibrated model for EERs was named the EERTEM (Elevated Experimental Raceway Temperature and Evaporation Model). The energy balance algorithms in the Biomass Assessment Tool (BAT model) were also added to the Python code and used to develop temperature simulations of standard commercial paddlewheel raceways. A comparison of BAT and EERTEM simulations indicated that EER temperature fluctuations are not representative of in ground commercial paddlewheel raceways, primarily due to the buffering effect of soil heat flux in commercial raceways. With the different temperature profiles, biomass productivities of three algae species in the EERs were compared to productivities in commercial raceways. Differences in productivity between EERTEM and BAT model temperature profiles were observed when the maximum daytime temperature of one raceway was in the optimal growth range but the temperature of the other raceway exceeded or was below the optimal growth range.

Khawam, George↗