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NASA NTRS1987

RE-1000 free-piston Stirling engine hydraulic output system description

The NASA Lewis Research Center was involved in free-piston Stirling engine research since 1976. Most of the work performed in-house was related to characterization of the RE-1000 engine. The data collected from the RE-1000 tests were intended to provide a data base for the validation of Stirling cycle simulations. The RE-1000 was originally build with a dashpot load system which did not convert the output of the engine into useful power, but was merely used as a load for the engine to work against during testing. As part of the interagency program between NASA Lewis and the Oak Ridge National Laboratory, (ORNL), the RE-1000 was converted into a configuration that produces useable hydraulic power. A goal of the hydraulic output conversion effort was to retain the same thermodynamic cycle that existed with the dashpot loaded engine. It was required that the design must provide a hermetic seal between the hydraulic fluid and the working gas of the engine. The design was completed and the hardware was fabricated. The RE-1000 was modified in 1985 to the hydraulic output configuration. The early part of the RE-1000 hydraulic output program consisted of modifying hardware and software to allow the engine to run at steady-state conditions. A complete description of the engine is presented in sufficient detail so that the device can be simulated on a computer. Tables are presented showing the masses of the oscillating components and key dimensions needed for modeling purposes. Graphs are used to indicate the spring rate of the diaphragms used to separate the helium of the working and bounce space from the hydraulic fluid.

Schreiber, Jeffrey G.↗

DOE OSTI2020

AlphaBuilding - Synthetic Buildings Operation Dataset

This is a synthetic building operation dataset which includes HVAC, lighting, miscellaneous electric loads (MELs) system operating conditions, occupant counts, environmental parameters, end-use and whole-building energy consumptions at 10-minute intervals. The data is created with 1395 annual simulations using the U.S. DOE detailed medium-sized reference office building, and 30 years' historical weather data in three typical climates including Miami, San Francisco, and Chicago. Three energy efficiency levels of the building and systems are considered. Assumptions regarding occupant movements, occupants' diverse temperature preferences, lighting, and MELs are adopted to reflect realistic building operations. A semantic building metadata schema - BRICK, is used to store the building metadata. The dataset is saved in a 1.2 TB of compressed HDF5 file. This dataset can be used in various applications, including building energy and load shape benchmarking, energy model calibration, evaluation of occupant and weather variability and their influences on building performance, algorithm development and testing for thermal and energy load prediction, model predictive control, policy development for reinforcement learning based building controls.

AlphaBuilding↗

DOE OSTI2020

Assessing uncertainty in the timing of energy use during cost-optimal distributed energy technology selection and sizing

This paper empirically derives uncertainty ranges in cost-optimal solar PV and storage sizing by comparing results from the REopt Lite optimization platform from metered data and a set of simulated Department of Energy Commercial Reference Building (CRB) profiles at 65 sites. We find load profile shape alone does not explain a site’s optimal configurations (i.e., PV, Storage, PV and Storage, No System). Still, load profile shape does introduce uncertainty to optimal PV and storage capacities. Across all cases where PV is part of an optimal configuration, we find the average ratio of power capacities derived from metered loads to capacities derived from CRB profiles to be 0.97 (and as high as 1463), where 1 would be a perfect match in system size. For storage, the ratio is 1.6 (and as high as 42). We also assess how, in the absence of complete metered data, a CRB profile can be selected that would be expected to yield the most similar solar PV and storage capacities. From those metrics that can be available from billing data (i.e., peak demand, monthly load totals), we find that uncertainty is most reduced by selecting the CRB’s with an annual peak occurring at the most similar time, or those with the lowest average root mean square error (RMSE) among monthly peak loads. This research can help improve the implementation and interpretation of results derived from simulated load profiles and is an important next step in advancing smart grid solutions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

PVwindow (Photovoltaic Window Simulator) [SWR-22-01]

PVwindow simulates photovoltaic window properties by allowing the user build stacks of thin film materials that compose the window layers. The only needed inputs are the complex refractive indices and thicknesses of the materials. The software will simulate the optical transmission, front reflection, and back reflection of the stack using the transfer matrix method. Properties specific to PV window optics such as visible transmittance and color are also calculated. The optics code extracts the number of absorbed photons in the PV absorber layer and solves the single diode equation to yield theoretical photovoltaic metrics such as power conversion efficiency, fill factor, open circuit voltage, and short circuit current of the PV window when illuminated at an arbitrary angle or from either side of the stack. The software tool ultimately allows researchers to design photovoltaic windows and simulate their properties. The software also exports files that can be read into LBL Window software or into the EnergyPlus and Open Studio building energy modeling software to determine larger scale energy impacts of PV window integration.

Wheeler, Lance↗

DOE OSTI2023

Simple Statistical Models for Predicting Overpressure Due to CO2 and Low-Salinity Waste-Fluid Injection into Deep Saline Formations

Deep saline aquifers have been used for waste-fluid disposal for decades and are the proposed targets for large-scale CO2 storage to mitigate CO2 concentration in the atmosphere. Due to relatively limited experience with CO2 injection in deep saline formations and given that the injection targets for CO2 sometimes are the same as waste-fluid disposal formations, it could be beneficial to model and compare both practices and learn from the waste-fluid disposal industry. In this paper, we model CO2 injection in the Patterson Field, which has been proposed as a site for storage of 50 Mt of industrial CO2 over 25 years. We propose general models that quickly screen the reservoir properties and calculate pressure changes near and far from the injection wellbore, accounting for variable reservoir properties. The reservoir properties we investigated were rock compressibility, injection rate, vertical-to-horizontal permeability ratio, average reservoir permeability and porosity, reservoir temperature and pressure, and the injectant total dissolved solids (TDS) in cases of waste-fluid injection. We used experimental design to select and perform simulation runs, performed a sensitivity analysis to identify the important variables on pressure build-up, and then fit a regression model to the simulation runs to obtain simple proxy models for changes in average reservoir pressure and bottomhole pressure. The CO2 injection created more pressure compared to saline waste-fluids, when similar mass was injected. However, we found a more significant pressure buildup at the caprock-reservoir interface and lower pressure buildup at the bottom of the reservoir when injecting CO2 compared with waste-fluid injection.

Ansari, Esmail↗

NASA NTRS2008

Design of an Indoor Sonic Boom Simulator at NASA Langley Research Center

Construction of a simulator to recreate the soundscape inside residential buildings exposed to sonic booms is scheduled to start during the summer of 2008 at NASA Langley Research Center. The new facility should be complete by the end of the year. The design of the simulator allows independent control of several factors that create the indoor soundscape. Variables that will be isolated include such factors as boom duration, overpressure, rise time, spectral shape, level of rattle, level of squeak, source of rattle and squeak, level of vibration and source of vibration. Test subjects inside the simulator will be asked to judge the simulated soundscape, which will represent realistic indoor boom exposure. Ultimately, this simulator will be used to develop a functional relationship between human response and the sound characteristics creating the indoor soundscape. A conceptual design has been developed by NASA personnel, and is currently being vetted through small-scale risk reduction tests that are being performed in-house. The purpose of this document is to introduce the conceptual design, identify how the indoor response will be simulated, briefly outline some of the risk reduction tests that have been completed to vet the design, and discuss the impact of these tests on the simulator design.

Klos, Jacob↗

DOE OSTI2014

Lesson Learned from Technical and Economic Performance Assessment and Benefit Evaluation of CHP-FCS

Recent efforts and interest in combined heat and power (CHP) have increased with the momentum provided by the federal government support for penetration of CHP systems. Combined heat and power fuel cell systems (CHP-FCSs) provide consistent electrical power and utilize the heat normally wasted in power generation for useful heating or cooling with lower emissions compared to alternative sources. A recent study investigated the utilization of CHP-FCSs in the range of 5 to 50KWe in various commercial building types and geographic locations. Electricity, heating, and water heating demands were obtained from simulation of the U.S. Department of Energy (DOE) commercial reference building models for various building types. Utility rates, cost of equipment, and system efficiency were used to examine economic payback in different scenarios. As a new technology in the early stages of adoption, CHP-FCSs are more expensive than alternative technologies, and the high capital cost of the CHP-FCSs results in a longer payback period than is typically acceptable for all but early-adopter market segments. However, the installation of these units as on-site power generators also provide several other benefits that make them attractive to building owners and operators. The business case for CHP-FCSs can be made more financially attractive through the provision of government incentives and when installed to support strategic infrastructure, such as military installations or data centers. The results presented in this paper intend to provide policy makers with information to define more customized incentives and tax credits based on a sample of building types and geographic locations in order to attract more business investment in this new technology.

Makhmalbaf, Atefe↗

DOE OSTI2021

Dynamic Building Load Control to Facilitate High Penetration of Solar Photovoltaic Generation (Final Technical Report)

Solar photovoltaic (PV) resources are the most common form of distributed generation in residential and commercial customer premises within electric distribution networks. A higher penetration of PV generation in distribution circuits will impose challenges on maintaining service voltages within the range of industry standards, power quality, and power flow. Buildings consume 74% of the electricity produced in the United States, and a significant portion of the building load is dispatchable, making them responsive to electrical grid needs. Oak Ridge National Laboratory—in collaboration with Southern Company; the University of Tennessee, Knoxville; and the Georgia Institute of Technology—is examining the PV integration issues in distribution-level electrical grids and developing integrated demand-side control and communication systems to enable responsive loads. The proposed responsive loads mechanism performs renewable generation following to increase the penetration of solar PV within each feeder. The specific objectives of this project are to (1) examine distribution-level PV integration scenarios to understand requirements, (2) undertake an end-to-end simulation-based design of a distributed control strategy of loads geographically near the PV generation asset to minimize the effect on the distribution feeder, (3) deploy and demonstrate the control technology developed in partnership with utilities, and (4) perform a scalability analysis at the utility scale. This 3-year integrated project aims to develop, demonstrate, and validate demand-side control technology to enable increased the penetration of renewables while mitigating challenges that arise due to their intermittency. Activities in Budget Period (BP) 1 focused on a literature review and the formal design of a control system for integrating local distribution with generation and loads. The team used modeling and simulation to evaluate the impact of varying buildings loads, variable PV generation, and power flow dynamics on the distribution circuit. The dynamic models developed in BP 1 were used in BP 2 to develop a model-based control design and a test bed. The test bed has enabled the simulation-based testing and comparison of different control designs and formulations applied to different configurations of the distribution grid, PVs, and building loads. The control approaches developed in BP 2 were implemented in BP 3 in the form of hardware deployed at the Central Baptist Church (CBC) in Knoxville, Tennessee, for testing and evaluation. The outcome of this project was the development and demonstration of open-source, low-cost, low-touch sensing and control retrofits to distributed PV generation and building loads that, in a coordinated fashion, provide the load-shaping response needed to integrate high levels of renewable penetration. This research addresses the target metrics by dynamically controlling a load with solar generation variability to minimize the extent of two-way power flow, enhance reliability, facilitate high PV penetration (>100% of peak load in a line segment), and generate scalable software and hardware solutions adaptable to any penetration levels. The research and development activities are focused and designed to be impactful within the relevant 2020 targets time frame.An accurate open-source integration simulation framework for end-to-end control design was developed and deployed at the CBC facility for testing and evaluation. This final report provides a detailed review of the technical results achieved during this 3-year integrated project. A novel spectral analysis of PV data is demonstrated to derive the requirements of the control design. A detailed simulation-based analysis of PV integration at increasing penetration levels is presented using 1 year of PV data to demonstrate the impact on the distribution circuits. Two different control strategies were developed and demonstrated via simulation to track variable PV generation with adaptive load dispatch. The report concludes with a summary of accomplishments and recommendations for a path forward.

14 SOLAR ENERGY↗

NASA NTRS1992

A domain-specific design architecture for composite material design and aircraft part redesign

Advanced composites have been targeted as a 'leapfrog' technology that would provide a unique global competitive position for U.S. industry. Composites are unique in the requirements for an integrated approach to designing, manufacturing, and marketing of products developed utilizing the new materials of construction. Numerous studies extending across the entire economic spectrum of the United States from aerospace to military to durable goods have identified composites as a 'key' technology. In general there have been two approaches to composite construction: build models of a given composite materials, then determine characteristics of the material via numerical simulation and empirical testing; and experience-directed construction of fabrication plans for building composites with given properties. The first route sets a goal to capture basic understanding of a device (the composite) by use of a rigorous mathematical model; the second attempts to capture the expertise about the process of fabricating a composite (to date) at a surface level typically expressed in a rule based system. From an AI perspective, these two research lines are attacking distinctly different problems, and both tracks have current limitations. The mathematical modeling approach has yielded a wealth of data but a large number of simplifying assumptions are needed to make numerical simulation tractable. Likewise, although surface level expertise about how to build a particular composite may yield important results, recent trends in the KBS area are towards augmenting surface level problem solving with deeper level knowledge. Many of the relative advantages of composites, e.g., the strength:weight ratio, is most prominent when the entire component is designed as a unitary piece. The bottleneck in undertaking such unitary design lies in the difficulty of the re-design task. Designing the fabrication protocols for a complex-shaped, thick section composite are currently very difficult. It is in fact this difficulty that our research will address.

Punch, W. F., III↗

DOE OSTI2022

Suppressing simulation bias in multi-modal data using transfer learning

Abstract Many problems in science and engineering require making predictions based on few observations. To build a robust predictive model, these sparse data may need to be augmented with simulated data, especially when the design space is multi-dimensional. Simulations, however, often suffer from an inherent bias. Estimation of this bias may be poorly constrained not only because of data sparsity, but also because traditional predictive models fit only one type of observed outputs, such as scalars or images, instead of all available output data modalities, which might have been acquired and simulated at great cost. To break this limitation and open up the path for multi-modal calibration, we propose to combine a novel, transfer learning technique for suppressing the bias with recent developments in deep learning, which allow building predictive models with multi-modal outputs. First, we train an initial neural network model on simulated data to learn important correlations between different output modalities and between simulation inputs and outputs. Then, the model is partially retrained, or transfer learned, to fit the experiments; a method that has never been implemented in this type of architecture. Using fewer than 10 inertial confinement fusion experiments for training, transfer learning systematically improves the simulation predictions while a simple output calibration, which we design as a baseline, makes the predictions worse. We also offer extensive cross-validation with real and carefully designed synthetic data. The method described in this paper can be applied to a wide range of problems that require transferring knowledge from simulations to the domain of experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2016

Energy Performance Assessment of Radiant Cooling System through Modeling and Calibration at Component Level

The paper describes a case study of an information technology office building with a radiant cooling system and a conventional variable air volume (VAV) system installed side by side so that performancecan be compared. First, a 3D model of the building involving architecture, occupancy, and HVAC operation was developed in EnergyPlus, a simulation tool. Second, a different calibration methodology was applied to develop the base case for assessing the energy saving potential. This paper details the calibration of the whole building energy model to the component level, including lighting, equipment, and HVAC components such as chillers, pumps, cooling towers, fans, etc. Also a new methodology for the systematic selection of influence parameter has been developed for the calibration of a simulated model which requires large time for the execution. The error at the whole building level [measured in mean bias error (MBE)] is 0.2%, and the coefficient of variation of root mean square error (CvRMSE) is 3.2%. The total errors in HVAC at the hourly are MBE = 8.7% and CvRMSE = 23.9%, which meet the criteria of ASHRAE 14 (2002) for hourly calibration. Different suggestions have been pointed out to generalize the energy saving of radiant cooling system through the existing building system. So a base case model was developed by using the calibrated model for quantifying the energy saving potential of the radiant cooling system. It was found that a base case radiant cooling system integrated with DOAS can save 28% energy compared with the conventional VAV system.

Building Energy Simulation↗

DOE OSTI2014

FINAL SCIENTIFIC REPORT Southwest United States of America – Distributed Technology Training Consortia (SWUSA-DTTC) Contract Number: DE-EE0006339

The Southwest United States of America – Distributed Technology Training Consortia (SWUSA-DTTC) leveraged the highest concentration of renewable resources in the U.S. as well as operation of the leading independent microgrid installations and other distributed technologies to collect and analyze real-time data streams, advance power system simulations and analysis, identify educational and training gaps and develop solutions-focused curricula. The SWUSA-DTTC consortium posed a unique collaboration between universities and utilities to ensure that classes were focused on subjects and topics of interest to the utilities and ones that had practical benefit related to the preparedness for accommodating high penetration of solar and other distributed energy technologies. This approach to have a close collaboration and shared effort to develop the course content and curriculum is unique and a significant departure from conventional course development. This coursework and training was intended to endure over a long time horizon (10-20 year time frame), and include professionals over the entire Southwest region and the rest of the US, and even outreach into foreign countries. Project Objectives In order to support the increase in power systems research, development, and analytical capacity, the SWUSA-DTTC brought together respected professors in Power Systems education, student/professor research and development, and valuable industry and utility experience. Through this program, the partnered universities created and/or modified existing curricula available to students and professionals in the form of university courses, short courses, videos, consortia-led training, and online materials. During this time, the supporting vendors and utilities provided the SWUSA-DTTC with technical advisory roles as well as providing input and feedback in terms of utility and related energy industry needs. The goals were to create power and energy systems training, curricula, and workforce preparedness through the inclusion of data collection and analysis, power systems expertise, and application-specific training activities which build on fundamental principles, modeling and simulation tools, field-immersed training and methods of performance validation. The outcome of the program was to result in better prepared and greater number of graduates ready to contribute to the field of power systems which depend upon the safe, reliable and efficient generation sources which make up an increasingly diverse mix of renewable power. Additionally, the program was to deliver critical training modules which are intended to support mid-career professionals and be woven into utility training programs used all over the country. Discontinuation Summary On September 29, 2014, Electricore received notice of discontinuation of federal funding under subject Award DE-EE0006339. DOE’s notice of discontinuation was the first indication provided to Electricore that the work completed against Task 1 - Program Planning and Evaluation during Budget Period 1 was inadequate. Significantly, the discontinuation was based in large part on the erroneous assertion that many of the tasks were incomplete as indicated in the Continuation Application. However, the Continuation Application was submitted July 29, 2014, while the period of performance for this last quarter in Budget Period 1 did not end until September 30, 2014. Accordingly, the performance for this last quarter in Budget Period 1 will be reported in the upcoming Quarterly Report which is not due until October 30, 2014. Nevertheless, in response to DOE’s letter and in further support of Electricore’s Continuation Application, we are providing a detailed status demonstrating adherence to all program requirements for each Task 1, Budget Period 1 SOPO activity and milestones in response to the DOE review.

14 SOLAR ENERGY↗

DOE OSTI2016

Time Constants for Optical Fiber Temperature Sensing using a Thermal Resistance Approach

Optical fibers are immune to electromagnetic interference, have no moving parts, no applied voltages, no special environmental conditions, and they are extremely small (100's of microns in diameter). The U.S. Department of Energy is interested in extending this technology to extremely high temperature radiation environments for the purposes of developing in-pile instrumentation for the restart of TREAT (Transient Reactor Test Facility). TREAT is an air-cooled, thermal, heterogeneous test reactor facility that was designed to evaluate reactor fuels and structural materials under conditions that simulate various types of transient overpower and under-cooling conditions that may be postulated to occur in a nuclear reactor. Spatially distributed temperature measurements can be made using an Optical Backscatter Reflectometer (such as, model 4600, manufactured by Luna Innovations, Inc.), coupled to single-mode optical fiber that is placed in an in-pile nuclear reactor testing facility. In-pile temperature sensing for the TREAT reactor will need to have a fast response to temperature changes, since the reactor pulse will be on the order of 100 msec. The sensors must also be robust enough to be installed in the testing facility; this requires the fibers to be in a protective capillary tubing that is made of a tough material, such as stainless steel. The temperature response of the fiber will be delayed by the capillary tubing. This paper discusses the characterization and modeling of the thermal time constants of the sensors. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2018

A Simplified Methodology to Estimate Energy Savings in Commercial Buildings from Improvements in Airtightness

Air leakage through the envelope of commercial buildings in the United States accounts for approximately 6% of their energy use. Various simulation approaches have been proposed to estimate the impact of air leakage on building energy use. Although approaches that are based on detailed airflow modeling appear to be the most accurate to calculate infiltration heat transfer in simulation models, these approaches tend to require significant modeling expertise and effort. To make these energy savings estimates more readily available to building owners and designers, Oak Ridge National Laboratory, the National Institute of Standards and Technology, the Air Barrier Association of America, and the US Department of Energy (DOE) are developing a user-friendly online calculator that applies a detailed airflow modeling approach to examine energy savings due to airtightness in commercial buildings. The calculator, however, is limited to 52 US cities and a few cities in Canada and China. This paper describes the development of an alternative, simplified method to estimate energy savings from improved airtightness. The proposed method uses the same detailed approach for hourly infiltration calculations as the online calculator but it expands the ability to estimate energy savings to all US cities using hourly outdoor air temperature as the only input. The new simple regression model-based approach was developed and tested with DOE’s standalone retail prototype building model. Results from the new approach and the calculator show good agreement. In addition, a simple approach to estimate percent energy savings for retrofitted buildings was also developed; results were within 5% of the energy saving estimates from the online calculator.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Advancing Building Energy Modeling with Large Language Models: Exploration and Case Studies

The rapid progression in artificial intelligence has facilitated the emergence of large language models like ChatGPT, offering potential applications extending into specialized engineering modeling, especially physics-based building energy modeling. This paper investigates the innovative integration of large language models with building energy modeling software, focusing specifically on the fusion of ChatGPT with EnergyPlus. A literature review is first conducted to reveal a growing trend of incorporating large language models in engineering modeling, albeit limited research on their application in building energy modeling. We underscore the potential of large language models in addressing building energy modeling challenges and outline potential applications including simulation input generation, simulation output analysis and visualization, conducting error analysis, co-simulation, simulation knowledge extraction and training, and simulation optimization. Three case studies reveal the transformative potential of large language models in automating and optimizing building energy modeling tasks, underscoring the pivotal role of artificial intelligence in advancing sustainable building practices and energy efficiency. The case studies demonstrate that selecting the right large language model techniques is essential to enhance performance and reduce engineering efforts. The findings advocate a multidisciplinary approach in future artificial intelligence research, with implications extending beyond building energy modeling to other specialized engineering modeling.

building energy modeling↗

DOE OSTI2026

From models to reality: a systematic review on simulated and measured residential heat pump energy savings

High-performance HVAC solutions are central to residential energy management. A substantial share of these are electric, reversible-cycle systems, with heat pumps representing the largest portion of current and near-term adoption. This review synthesizes peer-reviewed and grey literature on residential space heating and cooling heat pumps. The academic literature is dominated by modeling (73.8%), with limited field measurement (13.1%). Grey literature from United States serve as a supplemental resource providing measured savings. Conversions from electric-resistance heating consistently show the largest site energy reductions, while oil/propane baselines yield moderate savings, and gas baseline scenario often deliver small and region-dependent savings. This study cross-checks the grey literature measured data with simulation data filtered from the ResStock dataset. The comparison indicates a discrepancy between simulations and measured data: simulated site EUIs are typically lower than measured EUIs, but percentage energy savings fall in similar ranges, implying simulations capture directional effects while underestimating energy use. Factors associated with variability and model–measurement differences include system characterization and control representation (e.g., backup heat engagement, thermostat/setpoint strategies, commissioning/installation quality), occupant behavior, weather normalization, metering scope, and envelope characterization. This paper also outlines the proposed methodology for comparing simulation and measured data for heat pumps. It emphasizes the metrics used for comparison and units harmonization, building characteristics matching, and compact metadata are needed for simulations to match measured data. The proposed methodology is expected to improve the credibility of simulated savings as measured evidence grows.

Yu, Lili↗

DOE OSTI2020

Towards Trust-Augmented Visual Analytics for Data-Driven Energy Modeling

The promise of data-driven predictive modeling is being increasingly realized in various science and engineering disciplines, where experts are used to the more conventional, simulation-driven modeling practices. However, trust remains a bottleneck for greater adoption of machine learning-based models for domain experts, who might not be necessarily trained in data science. In this paper, we focus on the building energy domain, where physics-based simulations are being complemented or replaced by machine learning-based methods for forecasting energy supply and demand at various spatio-temporal scales. We study the trust problem in close collaboration with energy scientists and engineers and describe how visual analytics can be leveraged for alleviating this trust bottleneck for stakeholders with varying degrees of expertise and analytics goals in this domain.

Kandakatla, Akshith R.↗

DOE OSTI2020

Evaluating Implementations of the Immersed Boundary Method in the Weather Research and Forecasting Model

The terrain-following coordinate system used by many atmospheric models can cause numerical instabilities due to discretization errors as resolved terrain slopes increase and the grid becomes highly skewed. The immersed boundary (IB) method, which does not require the grid to conform to the terrain, has been shown to alleviate these errors, and has been used successfully for high-resolution atmospheric simulations over steep terrain, including vertical building surfaces. Since many previous applications of IB methods to atmospheric models have used very fine grid resolution (5 m or less), the present study seeks to evaluate IB method performance over a range of grid resolutions and aspect ratios. Two classes of IB algorithms, velocity reconstruction and shear stress reconstruction, are tested within the common framework of the Weather Research and Forecasting (WRF) Model. Performance is evaluated in two test cases, one with flat terrain and the other with the topography of Askervein Hill, both under neutrally stratified conditions. WRF-IB results are compared to similarity theory, observations, and native WRF results. Despite sensitivity to the location at which the IB intersects the model grid, the velocity reconstruction IB method shows consistent performance when used with a hybrid RANS/LES surface scheme. The shear stress reconstruction IB method is not sensitive to the grid intersection, but is less consistent and near-surface velocity errors can occur at coarse resolutions. This study represents an initial investigation of IB method variability across grid resolutions in WRF. Future work will focus on improving IB method performance at intermediate to coarse resolutions.

54 ENVIRONMENTAL SCIENCES↗