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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Optimization of Second Fault Detection Thresholds to Maximize Mission POS

In order to support manned spaceflight safety requirements, the Space Launch System (SLS) has defined program-level requirements for key systems to ensure successful operation under single fault conditions. To accommodate this with regards to Navigation, the SLS utilizes an internally redundant Inertial Navigation System (INS) with built-in capability to detect, isolate, and recover from first failure conditions and still maintain adherence to performance requirements. The unit utilizes multiple hardware- and software-level techniques to enable detection, isolation, and recovery from these events in terms of its built-in Fault Detection, Isolation, and Recovery (FDIR) algorithms. Successful operation is defined in terms of sufficient navigation accuracy at insertion while operating under worst case single sensor outages (gyroscope and accelerometer faults at launch). In addition to first fault detection and recovery, the SLS program has also levied requirements relating to the capability of the INS to detect a second fault, tracking any unacceptable uncertainty in knowledge of the vehicle's state. This detection functionality is required in order to feed abort analysis and ensure crew safety. Increases in navigation state error and sensor faults can drive the vehicle outside of its operational as-designed environments and outside of its performance envelope causing loss of mission, or worse, loss of crew. The criteria for operation under second faults allows for a larger set of achievable missions in terms of potential fault conditions, due to the INS operating at the edge of its capability. As this performance is defined and controlled at the vehicle level, it allows for the use of system level margins to increase probability of mission success on the operational edges of the design space. Due to the implications of the vehicle response to abort conditions (such as a potentially failed INS), it is important to consider a wide range of failure scenarios in terms of both magnitude and time. As such, the Navigation team is taking advantage of the INS's capability to schedule and change fault detection thresholds in flight. These values are optimized along a nominal trajectory in order to maximize probability of mission success, and reducing the probability of false positives (defined as when the INS would report a second fault condition resulting in loss of mission, but the vehicle would still meet insertion requirements within system-level margins). This paper will describe an optimization approach using Genetic Algorithms to tune the threshold parameters to maximize vehicle resilience to second fault events as a function of potential fault magnitude and time of fault over an ascent mission profile. The analysis approach, and performance assessment of the results will be presented to demonstrate the applicability of this process to second fault detection to maximize mission probability of success.

Anzalone, Evan↗
DOE OSTI2011

Task-parallel message passing interface implementation of Autodock4 for docking of very large databases of compounds using high-performance super-computers

A message passing interface (MPI)-based implementation (Autodock4.lga.MPI) of the grid-based docking program Autodock4 has been developed to allow simultaneous and independent docking of multiple compounds on up to thousands of central processing units (CPUs) using the Lamarkian genetic algorithm. The MPI version reads a single binary file containing precalculated grids that represent the protein-ligand interactions, i.e., van der Waals, electrostatic, and desolvation potentials, and needs only two input parameter files for the entire docking run. In comparison, the serial version of Autodock4 reads ASCII grid files and requires one parameter file per compound. The modifications performed result in significantly reduced input/output activity compared with the serial version. Autodock4.lga.MPI scales up to 8192 CPUs with a maximal overhead of 16.3%, of which two thirds is due to input/output operations and one third originates from MPI operations. The optimal docking strategy, which minimizes docking CPU time without lowering the quality of the database enrichments, comprises the docking of ligands preordered from the most to the least flexible and the assignment of the number of energy evaluations as a function of the number of rotatable bounds. In 24 h, on 8192 high-performance computing CPUs, the present MPI version would allow docking to a rigid protein of about 300K small flexible compounds or 11 million rigid compounds.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Study of Lower Emittance Lattices for SPEAR3

We study paths to significantly reduce the emittance of the SPEAR3 storage ring. Lattice possibilities are explored with the GLASS technique. New lattices are designed and optimized for practical dynamic aperture and beam lifetime. Various techniques are employed to optimize the nonlinear dynamics, including the Elegant-based genetic algorithm. Experimental studies are also carried out on the ring to validate the lattice design. The SPEAR3 storage ring is a third generation light source which has a racetrack layout with a circumference of 234.1 m. The requirement to maintain the photon beamline positions put a significant constraint on the lattice design. Consequently the emittance of SPEAR3 is not on par with some of the recently-built third generation light sources. The present operational lattice has an emittance of 10 nm. For the photon beam brightness of SSRL to remain competitive among the new or upgraded ring-based light sources, it is necessary to significantly reduce the emittance of SPEAR3. In this paper we report our ongoing effort to develop a lower emittance solution for SSRL. We first show the potential of the SPEAR3 lattice with results of the standard cell study using the GLASS technique. This is followed by a discussion of the design strategy for full-ring linear lattices. Several lattice options are compared. We then show the methods and results for dynamic aperture optimization. Experiments were also conducted on the SPEAR3 ring to implement the lattice and to measure the key lattice parameters.

43 PARTICLE ACCELERATORS↗
NASA NTRS2013

NASA Tech Briefs, April 2013

Topics covered include: Fully Integrated, Miniature, High-Frequency Flow Probe Utilizing MEMS Leadless SOI Technology; Nanoscale Surface Plasmonics Sensor With Nanofluidic Control; Advanced Dispersed Fringe Sensing Algorithm for Coarse Phasing Segmented Mirror Telescopes; Neural Network Back-Propagation Algorithm for Sensing Hypergols; Bulk Moisture and Salinity Sensor; Change-Based Satellite Monitoring Using Broad Coverage and Targetable Sensing; Circularly Polarized Microwave Antenna Element with Very Low Off-Axis Cross-Polarization; Ultra-Low Heat-Leak, High-Temperature Superconducting Current Leads for Space Applications; Flash Cracking Reactor for Waste Plastic Processing; An Automated Safe-to-Mate (ASTM) Tester; Wireless Chalcogenide Nanoionic-Based Radio-Frequency Switch; Compute Element and Interface Box for the Hazard Detection System; DOT Transmit Module; Composite Aerogel Multifoil Protective Shielding; Li-Ion Electrolytes with Improved Safety and Tolerance to High-Voltage Systems; Polymer-Reinforced, Non-Brittle, Lightweight Cryogenic Insulation; Controlled, Site-Specific Functionalization of Carbon Nanotubes with Diazonium Salts; Regenerable Sorbent for CO2 Removal; Sprayable Aerogel Bead Compositions With High Shear Flow Resistance and High Thermal Insulation Value; Lexan Linear Shaped Charge Holder with Magnets and Backing Plate; Robotic Ankle for Omnidirectional Rock Anchors; Wind, Wave, and Tidal Energy Without Power Conditioning; An Active Heater Control Concept to Meet IXO Type Mirror Module Thermal-Structural Distortion Requirement; Waterless Clothes-Cleaning Machine; Integrated Electrical Wire Insulation Repair System; LVGEMS Time-of-Flight Mass Spectrometry on Satellites; Surface Inspection Tool for Optical Detection of Surface Defects; Per-Pixel, Dual-Counter Scheme for Optical Communications; Certification-Based Process Analysis; Surface Navigation Using Optimized Waypoints and Particle Swarm Optimization; Smart-Divert Powered Descent Guidance to Avoid the Backshell Landing Dispersion Ellipse; Estimating Foreign-Object-Debris Density from Photogrammetry Data; Adaptive Sampling of Spatiotemporal Phenomena with Optimization Criteria; Building a 2.5D Digital Elevation Model From 2D Imagery; Eyes on the Earth 3D; Target Trailing With Safe Navigation for Maritime Autonomous Surface Vehicles; Adams-Based Rover Terramechanics and Mobility Simulator - ARTEMIS; ISTP CDF Skeleton Editor; Uplink Summary Generator (ULSGEN) Version 1.0; Robotics On-Board Trainer (ROBoT); Software Engineering Tools for Scientific Models; Automatic Data Filter Customization Using a Genetic Algorithm; Tracker Toolkit; Towards Efficient Scientific Data Management Using Cloud Storage; On a Formal Tool for Reasoning About Flight Software Cost Analysis; A Nanostructured Composites Thermal Switch Controls Internal and External Short Circuit in Lithium Ion Batteries; Spacecraft Crew Cabin Condensation Control; and Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex.

Source record↗
DOE OSTI2018

A genetic meta-algorithm-assisted inversion approach: hydrogeological study for the determination of volumetric rock properties and matrix and fluid parameters in unsaturated formations

An evolutionary inversion approach is suggested for the interpretation of nuclear and resistivity logs measured by direct-push tools in shallow unsaturated sediments. The efficiency of formation evaluation is improved by estimating simultaneously (1) the petrophysical properties that vary rapidly along a drill hole with depth and (2) the zone parameters that can be treated as constant, in one inversion procedure. In the workflow, the fractional volumes of water, air, matrix and clay are estimated in adjacent depths by linearized inversion, whereas the clay and matrix properties are updated using a float-encoded genetic meta-algorithm. The proposed inversion method provides an objective estimate of the zone parameters that appear in the tool response equations applied to solve the forward problem, which can significantly increase the reliability of the petrophysical model as opposed to setting these parameters arbitrarily. The global optimization meta-algorithm not only assures the best fit between the measured and calculated data but also gives a reliable solution, practically independent of the initial model, as laboratory data are unnecessary in the inversion procedure. The feasibility test uses engineering geophysical sounding logs observed in an unsaturated loessy-sandy formation in Hungary. The multi-borehole extension of the inversion technique is developed to determine the petrophysical properties and their estimation errors along a profile of drill holes. The genetic meta-algorithmic inversion method is recommended for hydrogeophysical logging applications of various kinds to automatically extract the volumetric ratios of rock and fluid constituents as well as the most important zone parameters in a reliable inversion procedure.

58 GEOSCIENCES↗
DOE OSTI2015

A harmonic pulse testing method for leakage detection in deep subsurface storage formations

Abstract Detection of leakage in deep geologic storage formations (e.g., carbon sequestration sites) is a challenging problem. This study investigates an easy‐to‐implement frequency domain leakage detection technology based on harmonic pulse testing (HPT). Unlike conventional constant‐rate pressure interference tests, HPT stimulates a reservoir using periodic injection rates. The fundamental principle underlying HPT‐based leakage detection is that leakage modifies a storage system's frequency response function, thus providing clues of system malfunction. During operations, routine HPTs can be conducted at multiple pulsing frequencies to obtain experimental frequency response functions, using which the possible time‐lapse changes are examined. In this work, a set of analytical frequency response solutions is derived for predicting system responses with and without leaks for single‐phase flow systems. Sensitivity studies show that HPT can effectively reveal the presence of leaks. A search procedure is then prescribed for locating the actual leaks using amplitude and phase information obtained from HPT, and the resulting optimization problem is solved using the genetic algorithm. For multiphase flows, the applicability of HPT‐based leakage detection procedure is exemplified numerically using a carbon sequestration problem. Results show that the detection procedure is applicable if the average reservoir conditions in the testing zone stay relatively constant during the tests, which is a working assumption under many other interpretation methods for pressure interference tests. HPT is a cost‐effective tool that only requires periodic modification of the nominal injection rate. Thus it can be incorporated into existing monitoring plans with little additional investment.

Sun, Alexander Y.↗
DOE OSTI2013

2nd World Congress on Integrated Computational Materials Engineering, Part II: Process Optimization: Multi-Objective Optimization of Microstructure in Wrought Magnesium Alloys.

The microstructural features that govern the mechanical properties of wrought magnesium alloys include grain size, crystallographic texture, and twinning. Several processes based on shear deformation have been developed that promote grain refinement, weakening of the basal texture, as well as the shift of the peak intensity away from the center of the basal pole figure — features that promote room temperature ductility in Mg alloys. At ORNL, we are currently exploring the concept of introducing nano-twins within sub-micron grains as a possible mechanism for simultaneously improving strength and ductility by exploiting a potential dislocation glide along the twin-matrix interface — a mechanism that was originally proposed for face-centered cubic materials. Specifically, we have developed an integrated modeling and optimization framework in order to identify the combinations of grain size, texture and twin spacing that can maximize strength-ductility combinations. A micromechanical model that relates microstructure to material strength is coupled with a failure model that relates ductility to a critical shear strain and a critical hydrostatic stress. The micro-mechanical model is combined with an optimization tool based on genetic algorithm. A multi-objective optimization technique is used to explore the strength-ductility space in a systematic fashion and identify optimum combinations of the microstructural parameters that will simultaneously maximize the strength-ductility in the alloy.

crystal plasticity↗
DOE OSTI2022

Broadband Asymmetric Transmission of Linearly Polarized Mid‐Infrared Light Based on Quasi‐3D Metamaterials

Abstract Metamaterials consisting of subwavelength resonators offer an exciting opportunity for realizing asymmetric transmission (AT) of linearly polarized light. However, to date, only moderate/narrow‐band AT responses have been obtained in metadevices based on stacked planar nanostructures. Here, leveraging a combination of a genetic algorithm (GA) based optimization method and a membrane projection lithography (MPL) fabrication approach, a quasi‐3D metamaterial for broadband AT of linearly polarized mid‐infrared light is demonstrated. Facilitated by the customized GA, an efficient exploration of 3D plasmonic meta‐atoms with broken mirror symmetry in the light propagation direction allows the satisfaction of the rigorous conditions for AT of linearly polarized waves over a broad wavelength range. Confirmed by surface current analysis, the observed AT behavior is attributed to the resonant coupling between the plasmonic nanostructures located on the two orthogonal walls of the MPL cavities. Incorporating an advanced inverse‐design method and a state‐of‐art fabrication technique, the methodology used in the present study provides a promising route for exploiting 3D metamaterials with sophisticated functionalities via effectively exploring the high‐dimensional parametric space offered by true 3D meta‐atoms.

Whiting, Eric B.↗
DOE OSTI2017

Novel Multiferroic Phases and Phenomena in Epitaxial (111) BiFeO 3 Films

Abstract Multiferroics are attracting much interest because they simultaneously possess ordered electric and magnetic dipoles. In particular, numerous recent studies are devoted to find novel multiferroic phases, as, for example evidenced by the flurry of activities that accompanied the discovery of the so‐called T‐phase in BiFeO 3 systems, when these latter are made in forms of (001) epitaxial films and subject to high‐enough compressive strains. Here it is predicted, via the combined use of a genetic algorithm and first‐principles calculations, that novel multiferroic phases, as well as new phenomena, can also occur in epitaxial BiFeO 3 films, but when grown along the less conventional [111] direction and when experiencing large enough tensile strains. One example includes the hexagonal YMnO 3 ‐type P6 3 cm phase, that exhibits an anomalous behavior for its out‐of‐plane electric polarization and that can also undergo magnetic transitions when varying the tensile strain. Another striking example is the emergence of an unusual crystal structure of triclinic symmetry, that possesses controllable polarization's direction as well as magnetic spiral structures whose characteristics (e.g., periodicity and propagation direction) can be altered by epitaxial strain. Such findings may open new ways to design multiferroics and novel devices exploiting their cross‐coupling between electric and magnetic properties.

Xu, Changsong↗
DOE OSTI2018

Theoretical Investigation of 2D Conductive Microporous Coordination Polymers as Li-S Battery Cathode with Ultrahigh Energy Density

Even though tremendous achievement has been made experimentally in the performance of lithium–sulfur (Li–S) battery, theoretical studies in this area are lagging behind due to the complexity of the Li–S systems and the effects of solvent. Because of this, a new methodology is developed for investigating the 2D hexaaminobenzene-based coordination polymers (2D-HAB-CPs) as cathode candidate materials for Li–S batteries via density functional theory calculations in combination with an in-house developed charge polarized solvent model and a genetic algorithm structure global search code. With high ratios of transition metal atoms and two-coordinated nitrogen atoms, excellent electric conductivity, and structural porosity, the 2D-HAB-CP is able to address all of the three main challenges facing Li–S batteries: confining the lithium polysulfides from dissolution, facilitating the electron conductivity and buffering the volumetric expansion during the lithiation process. In addition, the theoretical energy density of this system is as high as 1395 Wh kg -1 . These results demonstrate that the 2D-HAB-CP is a promising cathode material for Li–S batteries. The proposed computational framework not only opens a new avenue for understanding the key role played by solution and liquid electrolytes in Li–S batteries, but also can be generally applied to other processes with liquids involved.

25 ENERGY STORAGE↗
DOE OSTI2019

Computationally Driven Discovery of a Family of Layered LiNiB Polymorphs

Abstract Two novel lithium nickel boride polymorphs, RT ‐LiNiB and HT ‐LiNiB, with layered crystal structures are reported. This family of compounds was theoretically predicted by using the adaptive genetic algorithm (AGA) and subsequently synthesized by a hydride route with LiH as the lithium source. Unique among the known ternary transition‐metal borides, the LiNiB structures feature Li layers alternating with nearly planar [NiB] layers composed of Ni hexagonal rings with a B–B pair at the center. A comprehensive study using a combination of single crystal/synchrotron powder X‐ray diffraction, solid‐state 7 Li and 11 B NMR spectroscopy, scanning transmission electron microscopy, quantum‐chemical calculations, and magnetism has shed light on the intrinsic features of these polymorphic compounds. The unique layered structures of LiNiB compounds make them ultimate precursors for exfoliation studies, thus paving a way toward two‐dimensional transition‐metal borides, MBenes.

Gvozdetskyi, Volodymyr↗
DOE OSTI2019

Computationally Driven Discovery of a Family of Layered LiNiB Polymorphs

Abstract Two novel lithium nickel boride polymorphs, RT ‐LiNiB and HT ‐LiNiB, with layered crystal structures are reported. This family of compounds was theoretically predicted by using the adaptive genetic algorithm (AGA) and subsequently synthesized by a hydride route with LiH as the lithium source. Unique among the known ternary transition‐metal borides, the LiNiB structures feature Li layers alternating with nearly planar [NiB] layers composed of Ni hexagonal rings with a B–B pair at the center. A comprehensive study using a combination of single crystal/synchrotron powder X‐ray diffraction, solid‐state 7 Li and 11 B NMR spectroscopy, scanning transmission electron microscopy, quantum‐chemical calculations, and magnetism has shed light on the intrinsic features of these polymorphic compounds. The unique layered structures of LiNiB compounds make them ultimate precursors for exfoliation studies, thus paving a way toward two‐dimensional transition‐metal borides, MBenes.

Gvozdetskyi, Volodymyr↗
DOE OSTI2026

Modeling the Effects of Trimethylsilanol on Syngas Combustion Kinetics

A perturbation analysis modeling approach based on a genetic algorithm was used to identify possible reaction pathways to explain previous experimental observations of the strong acceleration of syngas auto-ignition by trimethylsilanol (TMSO). Organosilicon reactions were taken from an existing chemical kinetic mechanism for tetramethylsilane pyrolysis which also contained TMSO reactions. The experimental targets for optimization were ignition delay times and peak OH radical concentrations in the range 1010–1070 K, 5 atm with dilute (4%) ϕ = 0.1 syngas mixtures in N 2 /Ar containing 0, 200, and 1000 ppm TMSO. Hundreds of thousands of trials resulted in three models which accurately predicted the experimental auto-ignition times and peak OH concentrations. Rate of production analyses indicated that TMSO forms dimethylsilanediol, which then reacts creating two “catalytic loops.” The net effect of the loops is to accelerate the reaction H 2 + O = OH + H at a faster effective rate than H 2 /O 2 kinetics alone, thus enhancing the reactivity of syngas. The formation of the loops may be attributable to the high Si–C bond energies in siloxanols, reducing rates of thermal decomposition and allowing dimethylsilanediol to react with H 2 for a longer duration compared with its alkane analog. Here, the results of the current work provide valuable direction for fundamental studies of these new hypothesized reaction pathways.

Mansfield, Andrew B. [Eastern Michigan University,↗
DOE OSTI2025

Bridging Experiment and Theory to Reveal Compounds in K–Zn(Cd)–Bi Systems

This study investigates the facile hydride synthesis method guided by theoretical predictions to explore the K–T–Bi (T = Zn, Cd) phase spaces. Using an adaptive genetic algorithm (AGA) and density functional theory (DFT), candidate compositions are identified for experimental validation via a facile hydrides route, permitting experimental screening of K–Zn–Bi and “empty” K–Cd–Bi systems. The previously reported KZnBi and KZn 2 Bi 2 are synthesized alongside newly discovered KCdBi and KCd 2 Bi 2 . While the AGA and DFT predict the stability of these compounds, structural predictions align with the experiment only for KZnBi and KZn 2 Bi 2 . Single-crystal X-ray structure refinements confirm that KZnBi and KZn 2 Bi 2 adopt the hexagonal ZrBeSi- and tetragonal ThCr 2 Si 2 -structure types, respectively. KCdBi has tetragonal PbClF-structure type and KCd 2 Bi 2 belongs to the ThCr 2 Si 2 -structure type. A trend based on the ratio of the metal ionic radii allows to rationalize variation in the structure types within the ATBi family (A = Li–Cs), correctly identifying KCdBi as isostructural to NaZnBi. Thermal stability studied by high-temperature powder X-ray diffraction reveals that Zn-containing compounds melt at higher temperatures (821 K for KZn 2 Bi 2 ) than Cd-containing KCd 2 Bi 2 (635 K). This study highlights the efficacy of combining rapid synthesis techniques with predictive modeling, though structural predictions show some limitations in accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Constitutive model development of aluminum alloy 1100 for elevated temperature forming process

Commercially pure aluminum alloy, AA1100, presents good electrical and thermal conductivity, high formability, and low cost. Those favorable characteristics have the potential to enable bipolar plates with improved economics and enhanced performance compared to current stainless steel bipolar plates for proton exchange membrane fuel cells. An accurate constitutive model is essential to develop and optimize processing parameters and effectively control the forming process. Here, the objective of this work is to develop a constitutive model of AA1100 that is able to simulate stress-strain relation, formed geometry, and predict the onset of fracture strain to avoid forming failure. Initially, a set of tensile tests at temperature between 300 and 500°C and strain rate between 0.005 and 1.0/s were conducted to examine the deformation behavior. Then, a set of damage-based unified visco-plastic constitutive equations is proposed and calibrated based on the results of stress-strain data. A genetic algorithm optimization method is applied to search for best fitting material constants in constitutive equations. The proposed model shows good predictability of both the stress-strain relation and fracture strain at low strain rate and high temperature conditions. The accuracy of proposed model is also evaluated statistically. A comparison of the proposed model with three popular models (Arrhenius-type mode, Johnson-Cook model and Zerilli-Armstrong model) was made. The proposed model shows the best experimental agreement with correlation coefficient of 0.96 in contrast to 0.25, 0.38 and 0.75 for the popular models, respectively. The proposed model can help to optimize the elevated temperature forming process and guide die design to enable optimal geometric features in the formed components.

08 HYDROGEN↗
DOE OSTI2012

Bayesian Neural Networks for Uncertainty Analysis of Hydrologic Modeling: A Comparison of Two Schemes

Bayesian Neural Networks (BNNs) have been shown as useful tools to analyze modeling uncertainty of Neural Networks (NNs). This research focuses on the comparison of two BNNs. The first BNNs (BNN-I) use statistical methods to describe the characteristics of different uncertainty sources (input, parameter, and model structure) and integrate these uncertainties into a Markov Chain Monte Carlo (MCMC) framework to estimate total uncertainty. The second BNNs (BNN-II) lump all uncertainties into a single error term (i.e. the residual between model prediction and measurement). In this study, we propose a simple BNN-II, which use Genetic Algorithms (GA) and Bayesian Model Averaging (BMA) to calibrate Neural Networks with different structures (number of hidden units) and combine the predictions from different NNs to derive predictions and uncertainty analysis. We tested these two BNNs in two watersheds for daily and monthly hydrologic simulation. The BMA based BNNs developed in this study outperforms BNN-I in the two watersheds in terms of both accurate prediction and uncertainty estimation. These results show that, given incomplete understanding of the characteristics associated with each uncertainty source, the simple lumped error approach may yield better prediction and uncertainty estimation.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Performance-driven optimization of urban open space configuration in the cold-winter and hot-summer region of China

Urbanization has led to changes in urban morphology and climate, while urban open space has become an important ecological factor for evaluating the performance of urban development. This study presents an optimization approach using computational performance simulation. With a genetic algorithm using the Grasshopper tool, this study analyzed the layout and configuration of urban open space and its impact on the urban micro-climate under summer and winter conditions. The outdoor mean Universal Thermal Climate Index (UTCI) was applied as the performance indicator for evaluating the quality of the urban micro-climate. Two cases—one testbed and one real urban block in Nanjing, China -- were used to validate the computer-aided simulation process. The optimization results in the testbed showed UTCI values varied from 36.5 to 37.3 °C in summer and from -4.9 to -1.9 °C in winter. In the case of the real urban block, optimization results show, for summer, although the average UTCI value increased by 0.6 °C, the average air velocity increased by 0.2 m/s; while in winter, the average UTCI value increased by 1.7 °C and the average air velocity decreased by 0.2 m/s. These results demonstrate that the proposed computer-aided optimization process can improve the thermal comfort conditions of open space in urban blocks. Finally, this study discusses strategies and guidelines for the layout design of urban open space to improve urban environment comfort.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗