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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Effects of multiple simultaneous faults on characteristic fault detection features of a heat pump in cooling mode

Faults in air-cooled vapor compression air-conditioning systems are known to reduce performance, including efficiency, capacity, and lifespan. Their effects have been studied, and fault detection and diagnostic (FDD) methods have been developed as tools for field technicians to install or repair systems, or for monitoring to alert operators to the fault’s presence. Most of this work has focused on faults that occur singly. It is likely that in some systems, multiple faults occur simultaneously, but it is uncertain what effects this may have on diagnostics. Here, this paper describes a laboratory study of a split system air source heat pump in which combinations of two, three, and four simultaneous faults occur. The study includes all combinations of: improper evaporator airflow; overcharge or undercharge of refrigerant; liquid line restrictions; and non-condensable gas in the refrigerant, each at multiple fault intensities. Fault features – those characteristics that can be determined from measurements, for use in diagnostics – are analyzed, and the key fault features are presented. A robust existing method for determining refrigerant charge, the virtual refrigerant charge sensor (VRC) is tested using the multiple fault data, in order to understand how its performance is impacted by the combined faults. The VRC performs well, typically able to correctly determine whether a system is undercharged or overcharged, but the magnitude estimates are impacted. The results suggest that simple subcooling-based methods of charging a system are likely to provide unsatisfactory results when other faults are present.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Energy Performance Validation of a Gaseous Air Cleaning Technology for Commercial Buildings

The U.S. Department of Energy (DOE) Building Technologies Office Commercial Building Integration group conducts evaluations of new energy efficiency technologies as part of the High Impact Technology Catalyst program. The subject of this field validation project is an air cleaning technology that removes gaseous contaminants from indoor air to reduce outdoor air ventilation requirements. Reducing the volume of outdoor air required reduces heating, ventilating, and air conditioning (HVAC) loads and can provide significant energy savings for some buildings in certain climates. The technology, called the HLR (HVAC Load Reduction), was developed by enVerid. The technology uses a solid regenerable sorbent material that was developed by DOE's National Energy Technology Laboratory and licensed to the vendor for this application. The sorbent material was originally developed to adsorb carbon dioxide (CO2); the vendor continued to develop the sorbent and the overall system so that it can also remove volatile organic compounds (including aldehydes), carbon monoxide, ozone, and particulate matter 2.5 micrometers in diameter or smaller (PM2.5) from the air. This material has low regeneration temperature requirements, and its sorption properties are unaffected by humidity levels, both of which are beneficial for building applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Implementation and test of an automated control hunting fault correction algorithm in a fault detection and diagnostics tool

Control hunting due to improper proportional–integral–derivative (PID) parameters in the building automation system (BAS) is one of the most common faults identified in commercial buildings. It can cause suboptimal performance and early failure of heating, ventilation, and air conditioning (HVAC) equipment. Commercial fault detection and diagnostics (FDD) software represents one of the fastest growing market segments in smart building technologies in the United States. Implementation of PID retuning procedures as an auto-correction algorithm and integration into FDD software has the potential to mitigate control hunting across a heterogeneous portfolio of buildings with different BAS in a scalable way. This paper presents the development, implementation, and field testing of an automated control hunting fault correction algorithm based on lambda tuning open-loop rules. The algorithm was developed in a commercial FDD software and successfully tested among nine variable air volume boxes in an office building in the United States. The paper shows the feasibility of using FDD tools to automatically correct control hunting faults, discusses scalability considerations, and proposes a path forward for the HVAC industry and academia to further improve this technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Emulation and detection of physical faults and cyber-attacks on building energy systems through real-time hardware-in-the-loop experiments

The increasing use of remote or mobile access, integrated wearable technologies, data exchange, and cloud-based data analytics in modern smart buildings is steering the building industry towards open communication technologies. The increased connectivity and accessibility could lead to more cyber-attacks in smart buildings. On the other hand, physical faults (e.g., HVAC -heating, ventilation, and air-conditioning faults) may have similar adverse impacts as those from the cyber-attacks on building energy systems, such as occupant discomfort, energy wastage, and equipment downtime. However, current physical behavior-based anomaly detection methods fail to differentiate between cyber-attacks and physical faults in building energy systems. Moreover, the challenge in collecting real-world threat data with ground truth has led researchers to rely on numerical models with user-defined assumptions, which may not accurately reflect real-world conditions due to the lack of in-situ experimental datasets. To address these challenges and gaps, this paper presents a flexible hardware-in-the-loop (HIL) testbed for generating cyber-attack and physical fault datasets and demonstrating threat detection algorithms in a real building automation system (BAS) environment. This testbed combines hardware (i.e., real BAS with local HVAC controllers and a physical network) with software (i.e., high-fidelity models to represent behaviors of building envelope and HVAC energy systems), enabling emulations of realistic threats. Five HIL experiments, including one baseline without any threats, two with physical faults, and two with cyber-attacks, were conducted to generate datasets containing detailed network traffic and system states. A joint classification framework, incorporating a network analyzer and a physical HVAC fault detector, was proposed to automatically detect cyber-physical abnormalities on BAS at both the network and the physical HVAC levels. The network analyzer comprises a conditional random fields (CRF) based command validator and a statistics-based detection strategy. The fault detector employs a weather and schedule-based pattern matching and feature-based principal component analysis (WPM-FPCA) method. Evaluation of the classification using four metrics from the multi-class confusion matrix revealed an average accuracy of 90.2%, recall of 89.7%, precision of 88.5% and F1-score of 89.2%. Finally, these results demonstrate that the proposed joint classification framework can effectively differentiate between specific types of cyber-attacks (e.g., device reinitialization attack, network Denial-of-Service attack) and physical faults (e.g., air handling unit operational fault, cooling coil valve stuck) in real time for improved building energy management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Cabin Thermal Management Analysis for SuperTruck II Next-Generation Hybrid Electric Truck Design

In this article, we present a multistage, coupled thermal management simulation approach, informed by physical testing where available, to aid design decisions for PACCAR's SuperTruck II hybrid truck cabin concept. Focus areas include cabin insulation, battery sizing, and sleeper curtain position, as well as heating, ventilating, and air-conditioning (HVAC) component and accessory configurations, to maintain or improve thermal comfort while saving energy. The authors analyzed weather data and determined the national vehicle miles traveled weighted temperature and solar conditions for long-haul trucks. Example weather day profiles were selected to approximate the 5th and 95th percentile weighted conditions. A daylong drive cycle was developed to impose appropriate external wind conditions during rest and driving periods. Using the National Renewable Energy Laboratory's vehicle HVAC modeling and simulation tool VTCab, HVAC load design trade-off studies for the new truck geometry concept were completed. Parameters analyzed included effects of paint color, insulation, glass transmissivity, and curtain location. Simulation results helped with early design material selections for efficient cabin climate control. A detailed three-dimensional computer-aided engineering (CAE), computational fluid dynamics (CFD), radiation, and human physiology co-simulation, referred to in this article as CAE Thermal-CFD, was used to evaluate thermal comfort and energy impacts of diffuser configurations and air supply settings in driving and hoteling modes. Analysis revealed that it is more difficult to heat the cabin in hoteling mode during the winter than to cool the space in the summer. This seasonal load profile drives the requirement of additional energy storage for heating comfort. To determine the battery capacity requirement, multiday HVAC operation drive cycle simulations were then completed, showing that a 15-kWh battery would be required for HVAC operation during hoteling. Results helped reduce cabin thermal loads, determine component sizing requirements, and improve occupant comfort to save fuel and contribute to the economic viability of the hybrid system.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Molecular Additive Engineering for Process-Humidity Robustness and Reproducible Fabrication of Perovskite Solar Cells and Modules

The commercialization of perovskite solar cells (PSCs) faces significant challenges due to their sensitivity to environmental humidity, which compromises film crystallization and device stability. Here, we introduce diphenylvinylphosphine (DPVP) as a Lewis base additive that enhances the performance and reproducibility of PSCs fabricated under ambient-air conditions. DPVP suppresses moisture-induced defect formation and stabilizes crystallization within realistic process-humidity ranges (20–40% relative humidity) commonly encountered in laboratory and pilot-scale manufacturing environments. It improves film uniformity, reduces trap densities, and yields highly reproducible device performance, enabling champion PCEs of 24.2% in small-area devices and 20.5% in blade-coated 12 cm 2 mini-modules. Furthermore, DPVP-assisted modules exhibit enhanced stability, retaining over 85% of their initial efficiency after 900 h of maximum power point tracking (MPPT) at 65 °C. This study demonstrates a humidity-resilient and scalable additive strategy for ambient-air perovskite photovoltaic manufacturing.

defect passivation↗
DOE OSTI2025

Active multi-mode data analysis to improve fault diagnosis in AHUs

Faults in heating, ventilation and air conditioning systems can lead to increased energy consumption, occupant comfort issues, and reduced equipment lifetime. Commercial fault detection and diagnosis (FDD) tools has been increasingly deployed in U.S. commercial buildings. While they are helping to achieve energy efficiency and operational reliability, there remain gaps in their fault diagnostic capabilities. The diagnostic results often contain multiple distinct candidate root causes (CRCs) or offer no insight into CRCs. This study developed a novel active rule-based multi-mode data analysis method to enhance diagnostic resolution by applying proven rule sets and additional new rules to data from multiple known operational modes. The proposed method was demonstrated using enhanced air handling unit performance assessment rule sets and validated with the simulated data of two air handling units. New metrics, namely, reduced number of CRCs and improvement ratio, were developed to quantify the improvement of fault diagnostic resolution. The validation results showed that the proposed method effectively reduced the number of CRCs in contrast to analyzing data solely for a single mode of operation. It achieved a median improvement ratio of 80% in 19 test cases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Design complexity and performance analysis in additively manufactured heat exchangers

The main objective of this research is to investigate the tradeoffs between design complexity and thermal performance in additively manufactured metallic heat exchangers. Such heat exchangers have become a favorite topic for investigation in various fields ranging from air conditioning to aircraft gas turbine engines. In particular, high manufacturing cost has emerged as the major drawback in broad applications of manifold-microchannel heat exchanger (MMHXs). The possibility of cost-effective manufacturing has generated wide interest in applying additive manufacturing (AM) for fabricating MMHXs. Furthermore, AM technologies will provide an opportunity for enhanced design and superior heat transfer performance. In this study, innovative MMHXs are designed and fabricated through selective laser melting. An experimental setup was designed to measure pressure drop and heat transfer for the developed MMHXs with a wide range of Reynolds numbers. Furthermore, the coefficient of performance was calculated based on the heat flow rate, air pressure drop, and air flow rate. Measurement results demonstrated that in some scenarios adding more internal features, i.e., increasing design complexity, does not necessarily improve the MMHX performance.

10 SYNTHETIC FUELS↗
DOE OSTI2021

An Artificial-Intelligence and Machine-Learning-Based Methodology to Conduct Seemingly Strain-Controlled Fatigue Test in a Pressurized-Water-Reactor-Test-Loop-Autoclave, While Not Controlling the Strain

In general, low cycle fatigue analysis of pressurized water reactor (PWR) components, requires strain-controlled fatigue test data such as using strain versus life (ε–N) curves. Conducting strain-controlled fatigue tests under in-air conditions is not an issue. However, controlling strain in a PWR-test-loop-autoclave is a challenge, since an extensometer cannot be placed in a narrow autoclave (typically used in a high-temperature-pressure PWR-test-loop). This is due to lack of space inside an autoclave that houses the test specimen. In addition, installing a contact-type extensometer in the path of a high-pressure flow can be a challenge. These difficulties of using an extensometer inside an autoclave led us to use an outside-autoclave displacement sensor which measures the displacement of pull-rod-specimen assembly. However, in our study (based on in-air fatigue test data), we found that a pull-rod-controlled based fatigue test can lead to substantial cyclic hardening/softening resulting in substantially different cyclic strain amplitudes and their rates compared to the desired cyclic strain amplitudes and its rates. In this paper, we propose an Artificial-Intelligence and Machine-Learning based technique such as using k-means clustering technique to improve the pull-rod-control based fatigue test method, such that the gage-area strain amplitude and rates can reasonably be achieved. In support of this, we present the fatigue test results for both 316 SS base and 81/182 dissimilar-metal-weld specimens.

42 ENGINEERING↗
DOE OSTI2024

CAD-based Energy & Cost Models Prove Affordable Net Zero Energy Performance for WonderWindows + 24" On-center Framing

Windows are thermally the “weakest link” in the building envelope. Increasing the thermal resistance of windows can make buildings more energy efficient and reduce the cost of electricity needed for conditioning the building. The proper design and placement of framing can also help to reduce the thermal bridging that occurs near the window frame area. This study investigates the energy performance of multi-pane acrylic windows fitting 24" on-center framing. Initial parametric analysis is done for a single zone accessory dwelling unit (ADU). Then, an energy model was developed for three types of wood-framed buildings: townhomes, stacked flats and hotels. A whole building energy simulation is performed for each of these building types in hot-humid Houston, mixed-humid New York, and cold-humid Minneapolis climates. The results show up to a 39% reduction in heating, ventilation, and air-conditioning (HVAC) related electricity consumption for the cold climate compared to the Base case which has window and wall properties based on ASHRAE standard 90.1 2019. In the hot climate, a modest increase in electricity consumption was seen due to an increase in cooling electricity demand. The ADU achieved Net Zero Energy performance in all 3 Climate Zones despite having the highest exterior surface area-to-floor area ratio: the ADU also had the highest PV kW to floor area ratio compared to the other multi-story building types. The townhomes, hotel and stacked flats respectively met 73, 52 and 57 % of electrical use in Houston, 71, 48 and 56 % in New York, and 63, 40 and 53 % in Minneapolis from energy produced by rooftop solar. If 400 W solar panels are used instead of 320 W panel used for energy simulation, it is estimated that in the townhomes, hotel and stacked flats rooftop solar can meet 91, 65 and 71 % of electrical use in Houston; 89, 60 and 70% in New York, and 79, 50 and 66 % in Minneapolis. A preliminary evaluation of cost shows that such superior performance can potentially be achieved at less first cost with this 24"on-center solution than conventional construction. All the building types at the three locations used for simulation had net energy use intensity under 20 kBtu/sf/year with 320 W solar panel and under 17 kBtu/sf/year with 400 W solar panel. Further tailoring of building envelope R-values and window solar heat gain to particular Climate Zone locations for each building type shows promise in reducing the HVAC electricity use that comprises almost half of building energy use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Load Shifting with Space Conditioning Heat Pumps During Heating Season in the Pacific Northwest

Ductless mini- and multi-split heat pumps are commonly deployed in Pacific Northwest residences, which historically have inefficient space heating and no space cooling. Heat pumps provide these residences with more energy-efficient space heating in the winter and space cooling for increasingly warm summer periods. For many of these applications, heat pumps add a new electrical load at the residence, compelling regional utilities to seek to understand their impacts on the electrical grid and opportunities for load management. In coordination with regional utilities, this study examined the winter load-shifting potential of residential multi-split heat pumps with variable capacity technology. The study included nine residential sites with a total of 20 ductless indoor units, which underwent simulated smart grid control. Grid control functionality was provided through the CTA-2045 communication protocol and included offsetting temperature setpoints for individual indoor units in the study. Field data collection included whole-house and heating, ventilation, and air conditioning electrical power consumption; indoor zone temperatures; occupant surveys; and CTA-2045 curtailment data for both baseline and simulated load-shifting events by site. This paper provides an overview of the load-shifting strategies and aggregated results from winter data collection.

ASHRAE, Heat pump, energy effciency, residential b↗
DOE OSTI2024

Securing Grid-interactive Efficient Buildings (GEB) through Cyber Defense and Resilient System (CYDRES)

The DOE CYDRES project is driven by the urgent need to address critical research gaps in the domain of cyber-physical security of smart buildings, including Grid-interactive Efficient Buildings (GEBs). CYDRES, a real-time advanced building resilient platform, aims to enhance the cyber-attack-immune capabilities of buildings through multi-layered prevention, detection, and adaptation mechanisms. CYDRES consists of five key modules: a multi-layer network analyzer, an Automatic Fault Detection, Diagnosis, and Prognosis (AFDDP) framework, an intelligent mode selector, a cyber-resilient control framework, and a situation awareness platform. The Network Analyzer employs a data-driven framework that includes a protocol state learning tool and a CRF (Conditional Random Field) command validator. In Hardware-In-the-Loop (HIL) testbeds, it achieved 100% detection accuracy with a false alarm rate of 3%, validating its efficacy in identifying selected cyber-attacks. The AFDDP framework leverages pattern matching, PCA (Principal Component Analysis)-based strategies, and a DBN (Dynamic Bayesian Network)-based fault diagnosis approach to pinpoint the causes of physical system abnormalities using Building Automation System (BAS) data. In HIL experiments, the AFDDP module attained a detection accuracy of over 95% with a false alarm rate below 7%. Additionally, the fault detector utilized machine learning (Random Forest) and deep learning (Multi-Layer Perceptron) methods with acoustic sensor data to achieve a 100% fault detection accuracy in Heating, Ventilation, and Air-Conditioning (HVAC) equipment. The Mode Selector offered real-time impact analysis, allowing immediate actions to protect BASs in the face of emerging threats. The cyber-resilient control framework included an adaptive Model Predictive Control (MPC) and a measurement compensator, reducing temperature violations by up to 94% and improving the total demand flexibility by up to 70% in HIL experiments. Such HIL experiments covered a cyber-attack case and a physical fault case, showcasing CYDRES’ efficiency in maintaining operational continuity during threats. The situation awareness platform in Grafana enhanced real-time threat detection and response visualization, augmenting the operational awareness for building operators. CYDRES demonstrated high technical effectiveness in various test scenarios, particularly in HIL environments. The project's phased development approach ensured efficient use of resources, highlighting its practical feasibility and readiness for commercialization. By enhancing the security and resilience of building operations, CYDRES represents a significant advance in mitigating risks associated with cyber-physical systems, thereby enhancing public confidence in the safety of modern building infrastructure. Future directions for the project include expanding testing protocols, refining AFDDP methodologies, exploring more comprehensive resilient control strategies, and testing in real commercial buildings.

42 ENGINEERING↗
DOE OSTI2024

A Preliminary Investigation on the Performance of a Dual-Source Heat Pump using both the Air and the Ground

Air source heat pumps (ASHPs) and ground source heat pumps (GSHPs) are the two most common types of electric-driven heat pumps in the marketplace to replace fossil fuel-based heating systems. However, the performance and efficiency of ASHPs depend on the ambient air conditions. Therefore, ASHPs usually are equipped with electric resistance heaters to provide supplemental heating when the ambient temperature is low, and the heating demand is high. The electric resistance heaters could result in high power draws when they are turned on. On the other hand, due to the relatively steady temperature of the ground, GSHPs are more energy efficient than ASHPs when providing space heating and cooling to the buildings. However, the adoption of GSHP is hindered by its high initial cost, mostly due to the cost of drilling boreholes for installing ground heat exchangers (GHE). To solve the above issues, our study investigates the performance of dual-source heat pumps (DSHPs) with respect to that of ASHPs and GSHPs. The DSHP will use ambient air when its temperature is favorable for the efficient operation of the heat pump. When the ambient temperature is too hot or too cold, the ground source will be utilized to retain the high-efficiency operation of the heat pump. Because the cumulative thermal load of the GHE is shared with the ambient air, the size of the GHE could be smaller than those of the conventional GSHPs. The study will model the DSHP and simulate its performance in providing heating and cooling for a typical single-family house in regions with hot, mild, or cold climates. In addition, the required GHE size of the DSHP system will be determined through annual simulations and compared with that of conventional GSHPs.

Anees, Fady↗
DOE OSTI2020

Nationwide Energy Saving Potential Evaluation for Office Buildings with Occupant-Based Building Controls

The heating ventilation and air-conditioning (HVAC) system is a major contributor to building energy consumption. This paper aims to quantify the nationwide energy savings potential of implementing the occupancy-based control (OBC) for the HVAC system in typical medium-sized office buildings using a whole building simulation program (i.e., EnergyPlus). First, the medium-sized office from the DOE Commercial Prototype Building Models was modified to have detailed layout and space functions. Then, a statistic-algorithm-based tool was used to generate the dynamic occupancy schedules for various rooms. Next, both a baseline case and two OBC cases were created for the comparison based on the updated ASHRAE Standard 90.1 and ASHRAE Guideline 36. The HVAC operation in the baseline case follows a static occupancy schedule and fixed setpoint schedules for both room air temperatures and minimal system outside air flowrates, while the proposed OBC cases use the room temperature reset, system minimum outdoor airflow reset, and zone minimal supply airflow rate reset. These cases were extended to five climate zones in the United States to further quantify the energy savings potential associated with the OBC on a nationwide scale. The preliminary result of this case study shows that there could be significant energy savings potential from the proposed OBC strategies in medium-sized office buildings in the United States.

Pang, Zhihong↗
DOE OSTI2020

Energy Saving Quantification on Ductless Heat Pump (DHP) in Existing Homes

In residential retrofit applications, ductless mini-split heat pumps (DHP) are often reported to have high-energy savings potential, depending on the system they are supplementing or replacing. However, recently, there have been a number of utility studies and analyses indicating these energy savings are not being achieved when the existing system is left in place for backup heating or air conditioning. The Pacific Northwest National Laboratory conducted a three-phase project to help determine which control strategies would have the most energy savings impact in various climate zones around the United States. The first phase developed the standalone simulation model for the PNNL Lab Homes and investigated the energy-saving potential from different control strategies and HVAC system configurations. The second phase focused on conducting experiments in the PNNL Lab Homes, which tested the most promising solutions that were modeled in the first phase. The third phase used the field data to calibrate the simulation model and then extrapolated the results to different climate locations and different building sizes. This report focuses on the third phase of the study, including five major parts: model calibration, parametric model setup, results, a sensitivity analysis of air leakage rate, and conclusions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

A framework for calibrating and validating an air loop dynamic model in an HVAC system in Modelica

The use of Modelica for simulating the dynamic behaviors of building heating, ventilation, and air conditioning (HVAC) systems has gained popularity. Calibration of a model that represents large and complex HVAC systems in Modelica involves the determination of hundreds of parameters using real-world operation data. Considering the coupling effects among various components, such a calibration process is complex and time-consuming. In this study, we propose a systematic framework to efficiently calibrate and validate a complex HVAC system model in Modelica. The framework includes strategies to solicit real-system operation data and to decouple the model. The goal of this calibration framework is to accurately and efficiently determine a set of Modelica model parameters that provide a good match between the simulated and real system behaviors. To demonstrate the validity of the framework, it was applied to calibrate the parameters of a Modelica model of the air loop subsystem of a real AHU-VAV system. The results show that the calibrated model can generate simulated results, including VAV air flow rate, outdoor air flow, and fan power consumption, that match well with the operational data of the real system. The coefficient of the variation of the root mean square error, CV(RMSE), of the air flow rate and power consumption are 14.6 % and 11.5 %, respectively. The results prove that the framework is valid and effective, and it can be used to calibrate other complex HVAC system Modelica models in the future.

Li, Yicheng↗
DOE OSTI2024

Metal DiSulfide thin films synthesized by pulsed ion beam ablation: Self-assembled structures with improved mechanical properties in humid conditions

Thin films composed of transition metal dichalcogenides such as molybdenum disulfide (MoS 2 ) or tungsten disulfide (WS 2 ) are well known for their solid lubricating behavior in dry environments such as space, but deteriorate rapidly in environments where oxygen is present. There have been many attempts over recent decades to improve MoS 2 lubricating performance in humid environments by addition of metals such as titanium to the film. The additions have come in the form of co-sputtering with the MoS 2 , or formation of nano multilayer coatings. We have previously reported on the synthesis of MoS 2 films by high-power ion beam ablation [Prasad et al, Matls. Lett. 65 (2010) 4–6]. The resulting films are observed to contain spheres of pure Mo of 10–100 nm size evenly dispersed throughout the ~1 μm-thick film, a form of self-assembly not before seen in films produced by sputtering or by pulsed laser deposition (PLD). The remaining Mosingle bondS matrix was observed to crystalize in situ under frictional contact into MoS 2 with the basal planes orienting themselves in the direction of sliding underneath the wear surface. The present study concerns metal additions in the form of alternating layers with MoS 2 deposited in between from an ablation target. The addition of Ti resulted in the extension of good tribological performance to humid air conditions, but the path to good performance appears to be relatively narrow. The same distributed Mo spheres were present in the new film, and similar self-assembled morphologies when V was substituted for the Ti, and when multilayers were formed of WS 2 with Zr additions. Furthermore, it appears that addition of Ti resulted in improvements in mechanical film strength that contributed to the wear ability in humid conditions.

Intense ion beams↗
DOE OSTI2023

County-level assessment of behind-the-meter solar and storage to mitigate long duration power interruptions for residential customers

Customer concerns over electric system resilience could drive early adoption of behind-the-meter solar-plus-storage (BTM PVESS), especially as wildfire, hurricane, and other climate-driven risks to electric grids become more pronounced. However, the resilience benefits of BTM PVESS are poorly understood, especially for residential customers, owing to lack of data and methodological challenges, making it difficult to forecast adoption trends. In this paper, we develop a methodology to model the performance of BTM PVESS in providing backup power across a wide range of customer types, geography / climate conditions, and long duration power interruption scenarios, considering both whole-building backup and backup of specific critical loads. We combine novel, disaggregated end-use load profiles across the continental United States with temporally and geospatially aligned solar generation estimates. We then implement a PVESS dispatch algorithm to calculate the amount of load served during interruptions. We find that PVESS with 10 kWh of storage can meet a limited set of critical loads in most United States counties during any month of the year, though this capability drops to meeting only 86% of critical load, averaged across all counties and months, when heating and cooling are considered critical. Backup performance is lowest in winter months where electric heat is common (southeast and northwest U.S.) and in summer months in places with large cooling loads (southwest and southeast U.S.). Winter backup performance varies by roughly 20% depending on infiltration rates, while summer performance varies by close to 15% depending on the efficiency of the central air-conditioning system. Differences in temperature set-points in Harris County correspond to a 40% range in winter backup performance and a 20% range in summer performance. Economic calculations show that a customer’s resilience value of PVESS must be high to motivate adoption of these systems.

14 SOLAR ENERGY↗