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1. Model-driven Per-panel Solar Anomaly Detection for Residential Arrays

   https://doi.org/10.1145/3460236  

   Feng, Menghong; Bashir, Noman; Shenoy, Prashant; Irwin, David; Kosanovic, Beka (October 2021, ACM Transactions on Cyber-Physical Systems)

   null (Ed.)

   There has been significant growth in both utility-scale and residential-scale solar installations in recent years, driven by rapid technology improvements and falling prices. Unlike utility-scale solar farms that are professionally managed and maintained, smaller residential-scale installations often lack sensing and instrumentation for performance monitoring and fault detection. As a result, faults may go undetected for long periods of time, resulting in generation and revenue losses for the homeowner. In this article, we present SunDown, a sensorless approach designed to detect per-panel faults in residential solar arrays. SunDown does not require any new sensors for its fault detection and instead uses a model-driven approach that leverages correlations between the power produced by adjacent panels to detect deviations from expected behavior. SunDown can handle concurrent faults in multiple panels and perform anomaly classification to determine probable causes. Using two years of solar generation data from a real home and a manually generated dataset of multiple solar faults, we show that SunDown has a Mean Absolute Percentage Error of 2.98% when predicting per-panel output. Our results show that SunDown is able to detect and classify faults, including from snow cover, leaves and debris, and electrical failures with 99.13% accuracy, and can detect multiple concurrent faults with 97.2% accuracy. 

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2. Transient topology optimization for efficient design of actively cooled microvascular materials

   https://doi.org/10.1007/s00158-024-03774-2  

   Gorman, Jonathan; Pejman, Reza; Kumar, Sandeep R.; Patrick, Jason F.; Najafi, Ahmad R. (March 2024, Structural and Multidisciplinary Optimization)

   Abstract Microvascular materials containing internal microchannels are able to achieve multi-functionality by flowing different fluids through vasculature. Active cooling is one application to protect structural components and devices from thermal overload, which is critical to modern technology including electric vehicle battery packaging and solar panels on space probes. Creating thermally efficient vascular network designs requires state-of-the-art computational tools. Prior optimization schemes have only considered steady-state cooling, rendering a knowledge gap for time-varying heat transfer behavior. In this study, a transient topology optimization framework is presented to maximize the active-cooling performance and mitigate computational cost. Here, we optimize the channel layout so that coolant flowing within the vascular network can remove heat quickly and also provide a lower steady-state temperature. An objective function for this new transient formulation is proposed that minimizes the area beneath the average temperature versus time curve to simultaneously reduce the temperature and cooling time. The thermal response of the system is obtained through a transient Geometric Reduced Order Finite Element Model (GRO-FEM). The model is verified via a conjugate heat transfer simulation in commercial software and validated by an active-cooling experiment conducted on a 3D-printed microvascular metal. A transient sensitivity analysis is derived to provide the optimizer with analytical gradients of the objective function for further computational efficiency. Example problems are solved demonstrating the method’s ability to enhance cooling performance along with a comparison of transient versus steady-state optimization results. In this comparison, both the steady-state and transient frameworks delivered different designs with similar performance characteristics for the problems considered in this study. This latest computational framework provides a new thermal regulation toolbox for microvascular material designers. 

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3. LES Simulation of turbulent supercritical CO2 heat transfer in microchannels

   Nabil, M.; Rattner, A.S. (March 2018, 6th International Supercritical CO2 Power Cycles Symposium)

   Although supercritical CO2 (sCO2) heat transfer has been employed in industrial process since the 1960s, the underlying transport phenomenon in high-flux microscale geometries, as could be employed in concentrating solar receivers, is poorly understood. To date, nearly all experimental studies and simulations of supercritical convective heat transfer have focused on large diameter vertical channel and tube bundle flows, which may differ dramatically from microscale supercritical convection. Computational studies have primarily employed Reynolds averaged (RANS) turbulence modeling approaches, which may not capture effects from the sharply varying property trends of supercritical fluids. In this study, large eddy simulation (LES) turbulence modeling techniques are employed to study heat transfer characteristics of sCO2 in microscale heat exchangers. The simulation geometry consists of a microchannel of 750×737 μm cross-section and 5 mm length, heated from all four sides. Simulation cases are evaluated at reduced pressure P_r = 1.1, mass flux G = 1000 kg/m^2-s, heat flux q'' = 1.7 − 8.9 W/cm^2 , and varying inlet temperature: 20 − 100℃. Computational results reveal thermal transport mechanisms specific to microscale sCO2 flows. Results have been compared with available supercritical convection correlations to identify the most applicable heat transfer models for engineering of microchannel sCO2 heat exchangers. 

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4. Utilizing a novel mobile diagnostics lab to validate the impact of vegetative wall coverings in building cooling load reduction

   https://doi.org/10.1088/1742-6596/2069/1/012126  

   Fagbule, O; Patel, R; Passe, U; Thompson, J (November 2021, Journal of Physics: Conference Series)

   Abstract Building cooling loads are driven by heat gains through enclosures. This research identifies possible ways of reducing the building cooling loads through vegetative shading. Vegetative shading reduces heat gains by blocking radiation and by evaporative air cooling. Few measured data exist, so we gathered thermal data from a vegetative wall grown in front of a Mobile Diagnostics Lab (MDL), a trailer with one conditioned room with instrumentation that collects thermal data from heat flux sensors and thermistors within its walls. In spring 2020 a variety of plants were cultivated in a greenhouse and planted in front of the south façade of the MDL, which was placed in direct sunlight to collect heat flux data. The plants acted as a barrier for solar radiation and reduced the amount of thermal energy affecting the trailer surface. Data were collected through the use of 16 heat flux sensors and development of continuous infrared (IR) images indicating surface temperature with and without plant cover. The façade surface beneath the plants was 10-30 °C cooler than exposed façade areas. In further analyses, the heat-flux data were compared to IR temperature data. 

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5. Atmospheric Variability Drives Anomalies in the Bering Sea Air–Sea Heat Exchange

   https://doi.org/10.1175/JCLI-D-24-0105.1  

   Hayden, Emily_E; O’Neill, Larry_W; Zippel, Seth_F (December 2024, Journal of Climate)

   Abstract High latitudes, including the Bering Sea, are experiencing unprecedented rates of change. Long-term Bering Sea warming trends have been identified, and marine heatwaves (MHWs), event-scale elevated sea surface temperature (SST) extremes, have also increased in frequency and longevity in recent years. Recent work has shown that variability in air–sea coupling plays a dominant role in driving Bering Sea upper-ocean thermal variability and that surface forcing has driven an increase in the occurrence of positive ocean temperature anomalies since 2010. In this work, we characterize the drivers of the anomalous surface air–sea heat fluxes in the Bering Sea over the period 2010–22 using ERA5 fields. We show that the surface turbulent heat flux dominates the net surface heat flux variability from September to April and is primarily a result of near-surface air temperature and specific humidity anomalies. The airmass anomalies that account for the majority of the turbulent heat flux variability are a function of wind direction, with southerly (northerly) wind advecting anomalously warm (cool), moist (dry) air over the Bering Sea, resulting in positive (negative) surface turbulent flux anomalies. During the remaining months of the year, anomalies in the surface radiative fluxes account for the majority of the net surface heat flux variability and are a result of anomalous cloud coverage, anomalous lower-tropospheric virtual temperature, and sea ice coverage variability. Our results indicate that atmospheric variability drives much of the Bering Sea upper-ocean temperature variability through the mediation of the surface heat fluxes during the analysis period. Significance StatementA long-term ocean warming trend and a recent increase in marine heatwaves in the Bering Sea have been identified. Previous work showed that anomalies in the exchange of heat between the ocean and the atmosphere were the primary driver of Bering Sea temperature variability, but the processes responsible for the heat exchange anomalies were unknown. In this work, we show that the atmosphere is the primary driver of anomalies in the Bering Sea air–sea heat exchange and therefore plays an important role in altering the thermal state of the Bering Sea. Our results highlight the importance of understanding more about how the ocean and the atmosphere interact at high latitudes and how this relationship will be affected by future climate change. 

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