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Verification and validation of computational fluid dynamic simulations are performed at model and full scales for the high-speed littoral combat ship (LCS) surface combatant, including the effects of hook, interceptors, and water-jet propulsion. Predictions of the body force thrust, sinkage, and trim use a speed controller for attaining self-propulsion. Two methods for water-jet performance are used: 1) evaluation of forces based on integration of the stress over the wetted area of the hull and water-jet duct, pump casing, and nozzle (integral method) and 2) ITTC (2005) water-jet test procedure (control volume method). The comparison errors at model (resistance, sinkage, and trim) and full (power and trim) scales are satisfactory using both Froude (Fr) scaled model- and full-scale trial data, including the effects of the interceptors and water jets (WJ) on resistance/power, sinkage, and trim. For the model-scale model without WJS, the negative bottom hydro-dynamic pressure near the water-jet inlets are observed without and with the hook simulations, and experiments with the hook. The negative bottom vertical force near the water-jet inlets forthe simulations without the hook supports Savitsky's (2014) assertion that semi-displacement monohulls do not exhibit hydrodynamic lift and disproves Giles' (1992) assertion to the contrary. The hook and interceptors do not affect the pressure distribution significantly near the water-jet inlets. Forthe full scale model, the WJs induce bow up trim for the simulations and interpolated (between conditions)- and Fr scaled model-scale experiments. The negative bottom pressure and vertical force near the water-jet inlet forthe simulations disprove Giles' (1992) assertion that the WJs provide additional hydrodynamic lift. This is further supported by the comparisons of the vertical force % thrust vs. inlet velocity ratio forthe LCS, with results shown in Bulten (2005) for a high-speed motor yacht. Bulten (2005) shows positive vertical force for inlet velocity ratios ≥ 1.25. However, LCS operates in the regime of an inlet velocity ≤ 1.2; thus, consistent with Bulten (2005), the vertical force is negative. The nonlinear effects between the interceptors and WJs are small such that a linear combination can provide a reasonable approximation. [ABSTRACT FROM AUTHOR]

The shift toward urban decarbonization, which involves transitioning to heat pumps and integrating photovoltaic (PV) energy generation, poses substantial challenges to electricity grids in cities. Ithaca, NY, with its commitment to the Green New Deal, serves as a case study for cities confronted with these challenges. This paper explores how various building electrification scenarios might affect Ithaca's net-zero ambitions. We show that our reduced-order Urban Building Energy Modeling (UBEM) approach can accurately predict building energy consumption and rooftop solar PV energy generation for the 6114 buildings in the City of Ithaca. Building on that, we present three increasingly ambitious decarbonization scenarios that offer a holistic perspective on Ithaca's future electrification potential. In automating the reconstruction of building geometry from readily available LiDAR data, along with automated BEM setup and calibration, our methodology offers a robust toolkit to plan holistic decarbonization efforts. We argue that our approach, which forecasts both UBEM and PV for all residential and commercial buildings within a single framework, provides insights that cannot be reached with siloed methods. In the future, we believe that the abundance of readily available urban data sets will allow us to transition our approach to other jurisdictions across the US. • The monthly gas and electricity demand of 6114 buildings in Ithaca are modeled using UBEM. • We implement a validation approach via anonymized billing data that avoids privacy concerns. • We test three decarbonization scenarios regarding building electrification and photovoltaics • The scenarios offer top-level estimation of Ithaca's achieveable 'net zero days'. • Our fast scenario analysis provides a foundation for evaluating retrofitting interventions. [ABSTRACT FROM AUTHOR]

Urban form impacts the airflow patterns in cities and the resulting urban microclimate. This has significant implications for ventilation, overheating, wind chill, and safety concerns such as down drafts from skyscrapers. While Computational Fluid Dynamics (CFD) simulations are the best practice for analyzing urban airflow patterns in design, they are computationally expensive and require a high level of expertise, making them underutilized in the early design process. This paper presents a surrogate model for CFD using a Generative Adversarial Network (GAN) that can process arbitrary building geometries. The model is trained using an automated end-to-end pipeline based on Eddy3D and implemented within the Rhino and Grasshopper environment as an Open Neural Network Exchange (ONNX)-based CFD-GAN predictor. This workflow provides instantaneous simulation feedback within the design software, reduces the risk of user error, and allows for appropriate spatial resolution in early design. The CFD-GAN demonstrates promising accuracy, with a Structural Similarity Index Measure (SSIM) ranging from 75%–97% on a limited training dataset of 564 unique urban geometries. Although the model currently has limitations regarding accuracy in complex urban wake regions, we show that these are likely not of concern for outdoor thermal comfort analyses. While it cannot replace CFD in later design stages, the CFD-GAN facilitates the incorporation of urban airflow analysis in early design with minimal effort and instantaneous performance feedback. [Display omitted] • GAN surrogate model for urban CFD simulations processes arbitrary building geometries. • Automated end-to-end training pipeline utilizing Eddy3D produces modular ONNX-based CFD-GAN predictor. • CFD-GAN predictor integrated in Rhino & Grasshopper allows for seamless design workflow. • Achieved SSIMs ranging between 75%–97% based on 564 unique urban geometries. • Provides instantaneous simulation feedback for performance-driven decision-making in early urban design. [ABSTRACT FROM AUTHOR]

In this paper the authors present an algorithm that abstracts an arbitrarily shaped set of building volumes into a group of simplified ‘shoebox’ building energy models. It is shown that for generic perimeter and core floorplans the algorithm provides a faster but comparably accurate simulation results of annual load profiles vis-à-vis multi-zone thermal models generated according to ASHRAE90.1 Appendix G guidelines. Envisioned applications range from rapid thermal model generation for urban building energy modelling to schematic architectural design. Following a description of the algorithm, its ability to produce load profiles for a mixed-use neighborhood of 121 fully conditioned buildings for a variety of climates is demonstrated. The comparison yields relative mean square errors in simulated annual building energy use intensity of five to 10 percent compared to ASHRAE 90.1 compliant building energy models while reducing simulation times by a factor of 296. [ABSTRACT FROM AUTHOR]

An overview is provided of CFDShip-Iowa modeling, numerical methods and high performance computing (HPC), including both current V4.5 and V5.5 and next generation V6. Examples for naval architecture highlight capability and needs. High fidelity V6 simulations for ocean engineering and fundamental physics describe increased resolution for analysis of physics of fluids. Uncertainty quantification research is overviewed as the first step towards development stochastic optimization. [ABSTRACT FROM AUTHOR]

People spend approximately 90% of their lives indoors, and thus arguably, the indoor space design can significantly influence occupant well-being. Adequate views to the outside are one of the most cited indoor qualities related to occupant well-being. However, due to urbanization and densification trends, designers may have difficulties in providing vistas and views to the outside with an assortment of content, which can support the needs of their occupants. To better understand occupant view satisfaction and provide reliable design feedback to architects, existing view satisfaction data must be expanded to capture a wider variety of view scenarios and occupants. Most related research remains challenging in architectural practice due to a lack of easy-to-use early-design analysis tools. However, early assessment of view can be advantageous as design decisions in early design, such as building orientation, plan layout, and façade design, can improve the view quality. This paper, hence, presents results from a 181 participant view satisfaction survey with 590 window views. The survey data is used to train a tree-regression model to predict view satisfaction. The prediction performance was compared to an existing view assessment framework through case studies. The result showed that the new prediction (RMSE = 0.65) is more accurate to the surveyed result than the framework (RMSE = 3.78). Further, the prediction performance was generally high (R 2 ≥ 0.64) for most responses, verifying the reliability. To facilitate view analysis in early design, this paper describes integrating the satisfaction prediction model and a ray-casting tool to compute view parameters in the CAD environment. • Window view satisfaction data from 181 participants on diverse views were collected. • A new view parameter computing CAD tool was developed using ray-casting. • Tree-regression models predict occupant's view satisfactions with a high accuracy. • View satisfaction is highly related to sky view parameter and floor level. [ABSTRACT FROM AUTHOR]

The architectural community needs holistic, evidence-based planning tools to promote urban resilience in the face of global warming. To ensure maximum impact, simulation-driven microclimate analysis methods must be integrated early in the design process. With Eddy3D, we present a toolkit to simulate outdoor thermal comfort metrics with a decoupled approach. We motivate the decoupled systems framework with meteorological measurements and local and global sensitivity analyses of three different climates. For a real-world case study on a university campus, we present results for both wind velocity and mean radiant temperature simulations. Finally, we discuss the advantages and disadvantages of a decoupled simulation approach that considers design aiding for the architectural practice. Our findings support reduced simulation time and flexibility, with the caveat of reduced accuracy due to neglecting forced convection, albeit this being less relevant in the early stages of design. The framework presented in this manuscript has been implemented and released as Eddy3D, a plugin for Rhino & Grasshopper. [Display omitted] • We introduce Eddy3D — a toolkit for decoupled outdoor thermal comfort simulation that is motivated by global sensitivity analyses. • Eddy3D has been implemented as a plugin for Rhino & Grasshopper. • We validated both mean radiant temperature and wind velocity simulations with on-campus, real-world measurements — and show good agreement for both. • We discuss how our approach can help extract meaningful metrics such as the outdoor thermal comfort autonomy that help practitioners with performance-based decision aiding. [ABSTRACT FROM AUTHOR]

As global and local actors seek to address climate concerns, municipalities, regions, and countries are developing policies for the built environment to reach carbon neutrality. In most cases, however, current policies target new construction and operational carbon emissions only, thus omitting the significant carbon emission saving potential resulting from the reactivation of embodied carbon in existing buildings. This article describes the development of a high-resolution combined building stock model (BSM) and building energy model (BEM) on both building and urban scale using all residential buildings of Ithaca, NY, USA as a case study. The model offers a holistic, detailed and local perspective on operational and embodied carbon emissions, associated saving potentials at both the building and urban scale, and the linkages, trade-offs and synergies between buildings and energy use as a basis for decision-making. A circular economy (CE) in construction posited on the reuse and recycling of existing building materials, necessitates a detailed material inventory of the current building stock. However, the scale and nature of this endeavor preclude traditional survey methods. The modeling process described in this article instead engages a bottom-up data aggregation and analysis approach that combines detailed construction archetypes (CAs) and publicly available, higher-level municipal geospatial data with building metadata defining occupancy and systems to create an autogenerated, detailed 3D geometry. The resulting BSM and BEM can simulate both embodied carbon content and operational carbon emissions of individual buildings within a municipal study with minimal required input data and a feasible computational effort. This provides modelers with a new spatial and geometric fidelity to simulate holistic renewal efforts, and inform carbon neutrality policies and incentives towards the decarbonization of the built environment. [ABSTRACT FROM AUTHOR]

The Universal Thermal Climate Index (UTCI) has been linked to outdoor activity patterns and used to evaluate the effectiveness of urban interventions to improve thermal comfort. This study investigates how simulating the urban environment at increasing levels of physical accuracy impacts UTCI values along three cycling routes in Cambridge, Massachusetts. Baseline UTCI values are estimated using a local weather file, and the following increments in physical accuracy are considered: wind-scaling, shading from buildings, shading and cooling from trees, computational fluid dynamics simulations for wind speeds, and simulated surface temperatures. With bike ridership data from Bluebikes, Boston's bike-sharing program, the relationship between bike ridership patterns and UTCI values along each route is studied. Supervised machine learning models are applied to predict bike ridership based on UTCI and other predictors. UTCI simulation results show that incorporating the various increments of accuracy influences hourly UTCI values at urban areas and exposed areas differently. Incorporating local wind speeds is especially impactful for urban areas. The statistical models trained to predict hourly bike trip counts based on UTCI and other demand and weather predictors achieved a root-mean-squared error of 1.06 trips. 47% of predictions were correct, and an additional 42% of predictions were off by 1 trip. This study demonstrates the importance of spatial refinement in simulating UTCI, and motivates future research into efficient simulation methods or rules-of-thumb for deriving spatial-temporal UTCI values. Future work into building a robust predictive model would motivate the design of thermally comfortable environments for human-powered transportation in cities. [Display omitted] [ABSTRACT FROM AUTHOR]

Outdoor thermal comfort simulation simulations rely on the mean radiant temperature (MRT) seen by pedestrians as an important input that remains difficult to compute. Especially for large urban models, computing relevant surface temperatures and radiation fluxes that make up the MRT is a daunting task in terms of simulation setup and the computational overhead. We propose a new algorithm to estimate exterior surface temperatures of building facades, roofs, and ground surfaces in an arbitrary urban 3D model. The algorithm discretizes all model surfaces and clusters them by material properties and sky and sun exposure to reduce computational complexity. The model setup is fully automated, and the algorithm is implemented in the popular Rhino3d CAD environment. We demonstrate the accuracy of the algorithm by comparing both the resulting external surface temperatures against a high-fidelity simulation and the final MRT against real-world measurements. We report an RMSE of 1.8 °C and 2.0 °C, respectively, while reducing simulation times by a factor of ~80. Envisioned applications of the algorithm range from rapid microclimate simulations in fast-paced urban design processes to large scale urban comfort evaluation of existing cities. • New algorithm to predict exterior surface temperatures and MRT in an arbitrarily complex urban 3D model. • The algorithm is utilizing K-Means clustering to reduce simulation times by a factor of 80. • We report an RMSE of 1.8°C for surface temperature predictions of a full year. • Importance of long-wave radiation exchange is analyzed. • Largest heterogeneity in external surface temperature is reported for horizontal clusters close to obstacles and south-facing clusters. [ABSTRACT FROM AUTHOR]

Solar access is a crucial factor for the wellness and comfort of building occupants and for the development of the urban fabric. Most countries implemented regulatory frameworks that aim to guarantee appropriate access to sunlight into buildings. The solar envelope is a method that allows to determine the maximum buildout volume that guarantees solar access of neighboring buildings. Computer design tools have been developed to facilitate the automatic creation of solar envelopes. However, most of the tools have limitations when complex regulations need to be taken into account. The presented research develops an alternative computational method to generate solar envelopes to be used for different ordinances and particularly efficient in dense urban environments. Results show that the proposed method permits to obtain larger building masses than the conventional method, and to automate the generation of envelope variations, useful for assessing building performance and form selection in the early design stage. • The presented research develops an alternative method to generate solar envelopes named the Reverse Solar Envelope (RSE). • Differently than the conventional method the RSE method can be used in relation to different solar access ordinances. • The RSE method permits to generate larger solar envelopes than the conventional method especially in urban environments. • The workflow of the RSE generates automatically a number of solar envelopes for evaluation of building form alternatives. • The RSE method permits to automate the performance analysis process to improve building comfort and environmental impact. [ABSTRACT FROM AUTHOR]

This paper juxtaposes existing public policies and different planning paradigms with evidence from the first wave of the COVID-19 pandemic in New York City (NYC). Zip code tabulation area (ZCTA) data for NYC are used to address four main questions: (1) How do urban density and crowding affect infection rates? (2) How does the commuting environment relate to pandemic resilience? (3) How does the allocation of points of interest within a city impact the infection rate? (4) How do evident inequalities in a city influence vulnerability during a pandemic? The presented evidence is used to demonstrate that compact, well-mixed, and decentralized cities can increase pandemic resilience due to advantageous features such as short commute times and well-distributed points of interest. At the architectural level, more resilient apartment building typologies need to be developed to mitigate the ramifications of overcrowding. This analysis also reveals significant spatial disparities and how they disproportionally affect the pandemic risk of the vulnerable communities. These findings warrant a broader discussion on how urban design and planning can mitigate inequalities and transform cities into a resilient, inclusive, and sustainable urban environment. [ABSTRACT FROM AUTHOR]

• Annual outdoor thermal comfort evaluation workflow is introduced. • 60 typology and density scenarios in three hot climatic contexts were evaluated. • Annual energy balance and outdoor thermal comfort results were recorded iteratively. • The impact of urban form on energy performance and outdoor comfort is discussed. • This method helps integrate environmental quality considerations in urban design. With the rise of awareness of health and well-being in cities, urban environmental analysis should expand from energy performance to new environmental quality-based considerations. The limited potential to annually evaluate outdoor thermal comfort, predominant among these considerations, has restricted the exploration of the interrelations between urban morphology and annual energy performance. This study aims to bridge this gap by capitalizing on the new capabilities of Eddy3D – a Grasshopper plugin which enables effective calculations of hourly microclimatic wind factors via OpenFOAM which in turn are used to generate annual outdoor thermal comfort plots. Using this method, a parametric study was conducted for different typology and density scenarios in three different hot climatic contexts in Israel. The automated analytical workflow evaluated a total of 60 design iterations for their energy balance, outdoor thermal comfort autonomy (OTCA) and self-shading levels using the shade index. The high correlation found here between the annual shade index and the OTCA, across all climatic contexts, shows the potential of the shade index to serve as an effective indicator, in these contexts, for comparative or optimization outdoor comfort studies. Further results are both the superiority of the courtyard typology in both energy and outdoor comfort studies, and the contrasting impact of higher density on the annual energy balance (lower performance) and outdoor thermal comfort (higher performance) in hot climates. The annual plots of both the energy balance and OTCA reveal various seasonal and monthly trends in the three different climatic zones which can lead to localized and seasonal urban design strategies. [ABSTRACT FROM AUTHOR]