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At least 505 records · Page 28

Urban microclimate and its impact on building performance: A case study of San Francisco

Urban microclimate exerts an increasing influence on urban buildings, energy, and sustainability. This study uses 10-year measured hourly weather data at 27 sites in San Francisco, California, to (1) analyze and visualize the urban microclimate patterns and urban heat island effect; (2) simulate annual energy use and peak electricity demand of typical large office buildings and large hotels to investigate the influence of urban microclimate on building performance; (3) simulate indoor air temperature of a single-family house without air-conditioning during the record three-day heatwave of 2017, to quantify the divergence of climate resilience due to urban microclimate effect. Results show significant microclimate effects in San Francisco with up to 11 °C outdoor air temperature difference between the coastal and downtown areas on September 1, 2017, during the record three-day heatwave. The simulated energy results of the prototype large office and large hotel buildings using the 2017 weather data show over 100% difference in annual heating energy use and 65% difference in annual cooling energy use across different stations; as well as up to 30% difference in peak cooling electricity demand. The impacts on annual site or source energy use are minimal (less than 5%) as cooling and heating in a mild climate are a relatively small portion of overall building energy use in San Francisco. Results also show the microclimate effects influence indoor air temperature of unconditioned homes by up to 5 °C. Newer buildings and homes are much less affected by microclimate effects due to more stringent performance requirements of the building envelope and energy systems. Furthermore, these findings inform that San Francisco microclimate variations should be considered in urban energy planning, building energy codes and standards, as well as heat resilience policymaking.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Wildland Urban Interface (WUI) Emissions: Laboratory Measurement of Aerosol and Trace Gas from Combustion of Manufactured Building Materials

Wildfires are increasing in intensity and more often threatening the wildland urban interface (WUI) where buildings and homes coexist with the natural environment. WUI emissions have not been as well-studied as emissions from vegetation. Thus, there is a need to quantify the emissions of building materials used in home construction under flaming and smoldering conditions to study their impacts to human health, visibility, air quality, and climate. Here, in a controlled laboratory setting, we quantify emissions of aerosols and trace gases including formaldehyde, particulate matter, and black carbon. We focus on the combustion of traditional single-source wood-based construction fuels. Our results indicate that, similar to natural fuels, the aerosol optical properties were more related to combustion conditions than the fuel type. Overall, we observed significant variability in the gas and particle emissions. Consistent trends include high formaldehyde (HCHO) and carbon monoxide (CO) emissions for smoldering conditions and higher carbon dioxide (CO 2 ), nitrogen oxides (NO x ), and black carbon for flaming conditions. Finally, these observations highlight the need to better characterize emissions for materials in the built environment to assess large-scale climate and human health impacts of fires at the WUI.

54 ENVIRONMENTAL SCIENCES↗

Effect of specific non-pharmaceutical intervention policies on SARS-CoV-2 transmission in the counties of the United States

Non-pharmaceutical interventions (NPIs) remain the only widely available tool for controlling the ongoing SARS-CoV-2 pandemic. We estimated weekly values of the effective basic reproductive number (R eff ) using a mechanistic metapopulation model and associated these with county-level characteristics and NPIs in the United States (US). Interventions that included school and leisure activities closure and nursing home visiting bans were all associated with a median R eff below 1 when combined with either stay at home orders (median R eff 0.97, 95% confidence interval (CI) 0.58–1.39) or face masks (median R eff 0.97, 95% CI 0.58–1.39). While direct causal effects of interventions remain unclear, our results suggest that relaxation of some NPIs will need to be counterbalanced by continuation and/or implementation of others.

60 APPLIED LIFE SCIENCES↗

Development of a micro-combined heat and power powered by an opposed-piston engine in building applications

Residential homes and light commercial buildings usually require substantial heat and electricity simultaneously. A combined heat and power system enables more efficient and environmentally friendly energy usage than that achieved when heat and electricity are produced in separate processes. However, due to financial and space constraints, residential and light commercial buildings often limit the use of traditional large-scale industrial equipment. Here we develop a micro–combined heat and power system powered by an opposed-piston engine to simultaneously generate electricity and provide heat to residential homes or light commercial buildings. The developed prototype attains the maximum AC electrical efficiency of 35.2%. The electrical efficiency breaks the typical upper boundary of 30% for micro–combined heat and power systems using small internal combustion engines (i.e., <10 kW). Moreover, the developed prototype enables maximum combined electrical and thermal efficiencies greater than 93%. The prototype is optimally designed for natural gas but can also run renewable biogas and hydrogen, supporting the transition from current conventional fossil fuels to zero carbon emissions in the future. The analysis of the unit’s decarbonization and cost-saving potential indicate that, except for specific locations, the developed prototype might excel in achieving decarbonization and cost savings primarily in US northern and middle climate zones.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Charging infrastructure access and operation to reduce the grid impacts of deep electric vehicle adoption

Electric vehicles will contribute to emissions reductions in the United States, but their charging may challenge electricity grid operations. We present a data-driven, realistic model of charging demand that captures the diverse charging behaviours of future adopters in the US Western Interconnection. We study charging control and infrastructure build-out as critical factors shaping charging load and evaluate grid impact under rapid electric vehicle adoption with a detailed economic dispatch model of 2035 generation. We find that peak net electricity demand increases by up to 25% with forecast adoption and by 50% in a stress test with full electrification. Locally optimized controls and high home charging can strain the grid. Shifting instead to uncontrolled, daytime charging can reduce storage requirements, excess non-fossil fuel generation, ramping and emissions. Our results urge policymakers to reflect generation-level impacts in utility rates and deploy charging infrastructure that promotes a shift from home to daytime charging.

33 ADVANCED PROPULSION SYSTEMS↗

A high-fidelity residential building occupancy detection dataset

Abstract This paper describes development of a data acquisition system used to capture a range of occupancy related modalities from single-family residences, along with the dataset that was generated. The publicly available dataset includes: grayscale images at 32-by-32 pixels, captured every second; audio files, which have undergone processing to remove personally identifiable information; indoor environmental readings, captured every ten seconds; and ground truth binary occupancy status. The data acquisition system, coined the mobile human presence detection (HPDmobile) system, was deployed in six homes for a minimum duration of one month each, and captured all modalities from at least four different locations concurrently inside each home. The environmental modalities are available as captured, but to preserve the privacy and identity of the occupants, images were downsized and audio files went through a series of processing steps, as described in this paper. This dataset adds to a very small body of existing data, with applications to energy efficiency and indoor environmental quality.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An alternative domain-swapped structure of the Pyrococcus horikoshii PolII mini-intein

Protein splicing is a post-translational process by which an intein catalyzes its own excision from flanking polypeptides, or exteins, concomitant with extein ligation. Many inteins have nested homing endonuclease domains that facilitate their propagation into intein-less alleles, whereas other inteins lack the homing endonuclease (HEN) and are called mini-inteins. The mini-intein that interrupts the DNA PolII of Pyrococcus horikoshii has a linker region in place of the HEN domain that is shorter than the linker in a closely related intein from Pyrococcus abyssi. The P. horikoshii PolII intein requires a higher temperature for catalytic activity and is more stable to digestion by the thermostable protease thermolysin, suggesting that it is more rigid than the P. abyssi intein. We solved a crystal structure of the intein precursor that revealed a domain-swapped dimer. Inteins found as domain swapped dimers have been shown to promote intein-mediated protein alternative splicing, but the solved P. horikoshii PolII intein structure has an active site unlikely to be catalytically competent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spatial ecology of translocated raccoons

Raccoons (Procyon lotor) are routinely translocated both legally and illegally to mitigate conflicts with humans, which has contributed to the spread of rabies virus across eastern North America. The movement behavior of translocated raccoons has important ramifications for disease transmission yet remains understudied and poorly quantified. To examine the spatial ecology of raccoons following experimental translocation, we performed reciprocal 16 km-distance translocations of 30 raccoons between habitats of high and low raccoon density (bottomland hardwood and upland pine, respectively) across the Savannah River Site (SRS) in Aiken, South Carolina, USA (2018–2019). Translocation influenced patterns of raccoon space use, with translocated animals exhibiting a 13-fold increase in 95% utilization distributions (UDs) post- compared to pre-translocation (mean 95% UD 35.8 ± 36.1 km 2 vs 1.96 ± 1.17 km 2 ). Raccoons originating from upland pine habitats consistently had greater space use and larger nightly movement distances post-translocation compared to raccoons moved from bottomland hardwood habitats, whereas these differences were generally not observed prior to translocation. Estimated home ranges of male raccoons were twice the area as estimated for female raccoons, on average, and this pattern was not affected by translocation. After a transient period lasting on average 36.5 days (SD = 30.0, range = 3.25–92.8), raccoons often resumed pre-experiment movement behavior, with 95% UD sizes not different from those prior to translocation (mean = 2.27 ± 1.63km 2 ). Most animals established new home ranges after translocation, whereas three raccoons moved > 16 km from their release point back to the original capture location. Four animals crossed a 100-m wide river within the SRS post-translocation, but this behavior was not documented among collared raccoons prior to translocation. Large increases in space use combined with the crossing of geographic barriers such as rivers may lead to elevated contact rates with conspecifics, which can heighten disease transmission risks following translocation. These results provide additional insights regarding the potential impacts of raccoon translocation towards population level risks of rabies outbreaks and underscore the need to discourage mesocarnivore translocations to prevent further spread of wildlife rabies.

59 BASIC BIOLOGICAL SCIENCES↗

Measured indoor PM2.5, black carbon, and oxidative potential before and after replacing gas with induction cooking in asthmatic households

Cooking is a major source of fine particulate matter (PM) in homes and evidence to date is inconclusive about the impact of cooking fuel on measures of residential PM exposure. The Cooking Energy and Ventilation Impacts on Children's Asthma (CEVICA) study measured cooking frequency, range hood use, indoor air quality (IAQ) and respiratory health indicators of children with asthma living in homes with gas stoves in California's San Joaquin Valley. Intensive measurements occurred over three 2-week intensive periods: at baseline and at the end of two consecutive 3-month study phases. Participants were randomly assigned to have their gas stoves replaced with electric induction at the start of Phase 1 or Phase 2. As part of the IAQ assessment, we collected particulate matter on Teflon filters using ultrasonic personal air samplers (UPAS). The filters were analyzed to quantify time-integrated PM 2.5 mass concentration, black carbon (BC) oxidative potential (OP). OP was measured using the SLF-OH assay, an acellular chemical assay that quantifies production of OH radicals in simulated lung fluid (SLF). Across all comparisons, PM 2.5 mass tended to be higher during gas cooking than induction electric cooking, although only one transition (Baseline to Phase 1) was statistically discernible at p<0.05. BC and mass-normalized OP showed no measurable differences across stove types or across phases. These preliminary findings suggest that stove fuel alone may not be the dominant determinant of indoor PM 2.5 concentrations in this sample, as previous studies have reported that indoor PM 2.5 during cooking can also be influenced by factors such as cooking practices, food and oil type, kitchen ventilation, and outdoor infiltration.

Lin, Zhuoying↗

Experience with Rucio in the wider HEP community

Managing the data of scientific projects is an increasingly complicated challenge, which was historically met by developing experiment-specific solutions. However, the ever-growing data rates and requirements of even small experiments make this approach very difficult, if not prohibitive. In recent years, the scientific data management system Rucio has evolved into a successful open-source project that is now being used by many scientific communities and organisations. Rucio is incorporating the contributions and expertise of many scientific projects and is offering common features useful to a diverse re-search community. This article describes the recent experiences in operating Rucio, as well as contributions to the project, by ATLAS, Belle II, CMS, ES-CAPE, IGWN, LDMX, Folding@Home, and the UK's Science and Technology Facilities Council (STFC).

97 MATHEMATICS AND COMPUTING↗

Taming the fixed-node error in diffusion Monte Carlo via range separation

By combining density-functional theory (DFT) and wave function theory via the range separation (RS) of the interelectronic Coulomb operator, we obtain accurate fixed-node diffusion Monte Carlo (FN-DMC) energies with compact multi-determinant trial wave functions. In particular, we combine here short-range exchange-correlation functionals with a flavor of selected configuration interaction known as configuration interaction using a perturbative selection made iteratively (CIPSI), a scheme that we label RS-DFT-CIPSI. One of the take-home messages of the present study is that RS-DFT-CIPSI trial wave functions yield lower fixed-node energies with more compact multi-determinant expansions than CIPSI, especially for small basis sets. Indeed, as the CIPSI component of RS-DFT-CIPSI is relieved from describing the short-range part of the correlation hole around the electron-electron coalescence points, the number of determinants in the trial wave function required to reach a given accuracy is significantly reduced as compared to a conventional CIPSI calculation. Importantly, by performing various numerical experiments, we evidence that the RS-DFT scheme essentially plays the role of a simple Jastrow factor by mimicking short-range correlation effects, hence avoiding the burden of performing a stochastic optimization. Considering the 55 atomization energies of the Gaussian-1 benchmark set of molecules, we show that using a fixed value of mu = 0.5 bohr(-1) provides effective error cancellations as well as compact trial wave functions, making the present method a good candidate for the accurate description of large chemical systems.

Scemama, Anthony↗

Evolution of Superconducting-Transition Temperature with Superfluid Density and Conductivity in Pressurized Cuprate Superconductors

What factors fundamentally determine the value of superconducting transition temperature T c in high temperature superconductors has been the subject of intense debate. Following the establishment of an empirical law known as Homes' law, there is a growing consensus in the community that the T c value of the cuprate superconductors is closely linked to the superfluid density (ρ s ) of its ground state and the conductivity (σ) of its normal state. However, all the data supporting this empirical law (ρ s = AσT c ) have been obtained from the ambient-pressure superconductors. In this study, we present the first high-pressure results about the connection of the quantities of ρ s and σ with T c , through the studies on the Bi 1.74 Pb 0.38 Sr 1.88 CuO 6+δ and Bi 2 Sr 2 CaCu 2 O 8+δ , in which the value of their high-pressure resistivity (ρ = 1/σ) is achieved by adopting our newly established method, while the quantity of ρs is extracted using Homes' law. In conclusion, we highlight that the T c values are strongly linked to the joint response factors of magnetic field and electric field, i.e., ρ s and σ, respectively, implying that the physics determining T c is governed by the intrinsic electromagnetic fields of the system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Estimating the electric vehicle charging demand of multi-unit dwelling residents in the United States

Abstract Early battery electric vehicle (EV) adopters can access home chargers for reliable charging. As the EV market grows, residents of multi-unit dwellings (MUDs) may face barriers in owning EVs and charging them without garage or parking availability. To investigate the mechanisms that can bridge existing disparities in home charging and station deployment, we characterized the travel behavior of MUD residents and estimated their EV residential charging demand. This study classifies the travel patterns of MUD residents by fusing trip diary data from the National Household Travel Survey and housing features from the American Housing Survey. A hierarchical agglomerative clustering method was used to cluster apartment complex residents’ travel profiles, considering attributes such as dwell time, daily vehicle miles traveled (VMT), income, and their residences’ US census division. We propose a charging decision model to determine the charging station placement demand in MUDs and the charging energy volume expected to be consumed, assuming that MUD drivers universally operate EVs in urban communities. Numerical experiments were conducted to gain insight into the charging demand of MUD residents in the US. We found that charging availability is indispensable for households that set out to meet 80% state of charge by the end of the day. When maintaining a 20% comfortable state of charge the entire day, the higher the VMT are, the greater the share of charging demand and the greater the energy use in MUD chargers. The upper-income group requires a greater share of MUD charging and greater daily kWh charged because of more VMT.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A Behavior Tree Approach for Battery-Aware Inspection of Large Structures Using Drones

Electric multi-rotor drones have been used to inspect several structures, including large buildings and dams. In these inspections, energy consumption is a concern. To prevent the drone from running out of battery, commercial drones usually come back to their home position when the battery level reaches a minimum threshold. The pilots then need to replace the battery and use their own experience to restart the inspection mission approximately from where it ended before the drone returned home. Instead of relying on the human operator, in this paper, we automate this process using behavior trees, which is an effective way to perform autonomous mission control and supervision. By integrating battery management strategies into a behavior tree framework, this paper demonstrates the drone’s adaptive and resilient decision-making when confronted with limited power constraints. We implemented our methodology using a commercial drone and tested the proposed ideas in a photogrammetry-based inspection task.

42 ENGINEERING↗

Real-Time MPC for Residential Building Water Heater Systems to Support the Electric Grid

The world of IoT (internet of things) is spawning new control options and decision making that has not been available before. This is providing a wealth of opportunities for transactive type controls and systems that can negotiate for a common goal. This paper discusses a transactive residential neighborhood with optimization at the home level utilizing a system of agents. The real-time optimization utilizes information and modeling to optimize heat pump water heater operation in occupied homes. Data is presented showing the performance of the optimization and conclusions are drawn on next steps for development.

Starke, Michael↗

Using Temporal Information from Human Mobility Data to Detect Anchor Points

Spatiotemporal mobility data are available in massive quantities, but large quantities of data typically include fewer variables or data fields. Often, the only available fields are User ID, Longitude, Latitude, Timestamp (ULLT). This raises an important question: how much can we infer about human mobility patterns using only these four fields? With ULLT data, we do not know individuals' socioeconomic status information or when they are visiting their anchor points (AP) or locations (such as homes, places of employment, or schools), and it is a modern challenge to use this data to infer these characteristics. When detecting anchor locations with limited input information, verification and validation (VV) are significant challenges. This paper addresses the problem of identifying individuals' anchor locations using only temporal information from spatiotemporal datasets with limited attributes. Our approach does not explicitly use latitude and longitude during analysis. Locationbased information is only employed in the preprocessing stage to identify periods of movement (trips) and stops (dwelling). Beyond this step, all analysis is based on temporal patterns. In theory, if stops and dwell times could be detected through alternative means, our method could function entirely without location-based input. We demonstrate this methodology on the 2017 National Household Travel Survey (NHTS) data, because it includes a carefully designed and collected time use survey with representative sampling and labeled ground truth. The high-quality survey data allows us to test the accuracy of our methods because NHTS contains intended place labels and agent/user characteristics. We have also applied our validated AP identification algorithm on very large-scale GPS based trajectory data for Patterns-of-Life (PoL) assessment and other applications, but due to space limit that could not be presented here.

McBride, Liz [ORNL] (ORCID:0000000286925869)↗

Peak Reduction in a Residential Community Through Bayesian Optimization of Transactive Control Signals

Daily residential power consumption in aggregate tends to have a large peak that places stress on the distribution system and induces high operational costs. This work shows that coordinated transactive control of noncritical loads within a residential community or microgrid can help to alleviate peak-time stress on the distribution system by flattening the aggregate load curve. Treating the load forecaster as a high-fidelity, expensive black-box function, a new algorithm utilizing Bayesian optimization (BO) is proposed to achieve the best solution under uncertainty with minimal computing effort. The proposed BO algorithm manipulates the shape of the load based on transactive signals sent to each home. The thermostatically controlled loads (TCLs) act out of self-interest in response to the given price while maintaining comfort, and the optimizer exploits the thermal energy retention of the homes for the benefit of the community. Simulations confirm consistent neighborhood-level peak power reduction and energy cost savings.

Schomer, Ian↗

Impacts of Experimentally Obtained Harmonic Spectrums of Residential Appliances on Distribution Feeder

Owing to the increased use of power electronic based appliances and energy-efficient home equipment such as modern lighting loads, the percentage of nonlinear loads has increased in the distribution system, which can impact system performance, loss, and stability. Thus a comprehensive knowledge of their power quality and harmonic analysis is essential to improve the load models, voltage stability assessment, determination of possible interactions at harmonic frequencies, protection planning, and the effect of system impedance. This paper focuses on harmonic load flow analysis for multiple residential load types to determine the expected impacts on an modeled distribution secondary. For this study, the household appliances include lighting, power electronic, resistive, and motor loads with a nominal supply voltage of 120 V single-phase or 240 V split phase at a nominal frequency of 60 Hz. The harmonic spectrums, as obtained from the experimental evaluation of real loads, are used to inform the harmonic load flow for a detailed secondary network, including the distribution service transformer extracted from a real distribution feeder's model. Additionally, the impact of voltage harmonics on a three-phase test load is presented with experimental results. The harmonic data of the transformer terminal voltage, as obtained from the former load flow study, are scaled to generate the source voltage for the three-phase configuration of the grid simulator to make the test setup very similar to a typical secondary design in the U.S.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗