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The current testing and rating procedure for residential air conditioners and heat pumps is based on a steady-state performance measurement approach with a degradation coefficient to account for cycling losses at part-load conditions. Test equipment performance is measured under various ambient conditions with varying compressor and fan speeds, and the results are propagated through a temperature-bin method to estimate seasonal performance. Although the current rating approach offers a standardized performance metric for comparing the relative performances of different equipment, it involves disabling the native controls and, as a result, does not consider the impact of integrated controls for test units and their dynamic interactions with representative building loads. As an alternative, a load-based testing methodology (CSA EXP07) has been developed in which the dynamic performance of equipment is measured in a test facility by allowing it to respond to a simulated virtual building model. This study compares the steady-state and dynamic load-based performance measurement methodologies for use on a 5-ton residential heat pump system in order to understand the differences and their significance for the next-generation rating procedure. The differences in the two test methodologies' performance evaluation results are discussed with a causal analysis of the observed differences. [ABSTRACT FROM AUTHOR]

Improving the energy efficiency of air conditioners and heat pumps is crucial for reducing the effects of continuously rising energy demands for space conditioning. One of the effective and tested approaches for achieving this goal has been to set energy efficiency benchmarks based on minimum energy performance standards which drive technological innovation and implementation in the market. For heat pumps, a testing and rating procedure that estimates equipment seasonal performance from laboratory measurements forms the technical basis for these standards. However, with current residential heat pumps rating standards, significant differences have been observed between efficiency measured in the lab and actual operational performance in field applications. One of the reasons for this is that with current rating approaches, the test unit native controls are overridden when measuring performance in the laboratory. As an alternative, a load-based testing approach has been developed that captures dynamic interactions of the integrated controls, equipment and building with the goal of better-representing field application conditions. In this paper, a load-based testing approach previously developed for air-conditioners is extended for heat–pump heating-mode and demonstrated for a variable-speed system. Climate-specific heating seasonal performance ratings were determined by propagating the test results through a temperature-bin method. [ABSTRACT FROM AUTHOR]

• A load-based testing and performance rating approach for residential cooling equipment is developed. • Test equipment with its native controls behaves as if it were installed in the field. • Test is automated by implementing standardized procedures and convergence criteria. • Climate-specific seasonal performance ratings are generated from test results. • The proposed approach was implemented to a variable-speed heat pump. In the U.S., with about 64% of primary occupied homes having unitary air conditioners, a small improvement in the energy efficiency of residential cooling equipment can lead to significant energy savings. Currently, standardized equipment energy efficiency rating is based on standard AHRI 210/240, that provides a metric for comparing the performance of different equipment. However, it is generally recognized that this approach fails to appropriately rate and credit equipment with advanced controls and variable-speed components. Contrarily, a load-based testing and rating approach is presented in this paper that can capture equipment performance with its integrated controls that is more representative of the field. In this approach, representative building sensible and latent loads are emulated in a psychrometric test facility at different indoor and outdoor test conditions utilizing a virtual building model. The indoor test room conditions are continuously adjusted to emulate the dynamic response of the virtual building to the test equipment sensible and latent cooling rates and the equipment dynamic response is measured. Moreover, an automated testing procedure is presented along with convergence criteria for measuring equipment steady-periodic performance. Climate-specific cooling seasonal performance ratings can be determined by propagating the coefficient of performance (COP) from load-based testing results through a temperature-bin method to estimate a seasonal COP (SCOP). In this work, the proposed approach was implemented to test and rate a variable-speed residential heat pump. Furthermore, the sensitivity of load-based testing results to virtual building parameters was investigated. Finally, repeatability results from the load-based testing approach are presented. [ABSTRACT FROM AUTHOR]

• Validate the dynamic load-based testing and rating methodology for residential heat pumps. • Compare the dynamic performance of a heat pump measured in a residential house facility with that measured in a psychrometric test laboratory. • The simplified virtual building modeling approach effectively characterizes the load and dynamics of a typical residential building. • The load-based testing methodology accurately characterizes the heat pump dynamic performance in the lab compared to the residential house. A load-based testing method has been proposed to measure the overall dynamic performance of heat pumps and air conditioners, including their embedded controls and thermostats, in a laboratory setting. This method enables a test unit to respond to field-representative conditions emulated using a virtual building model. To adopt this methodology for next-generation rating standards, it is necessary to evaluate its ability to accurately capture a system's dynamic performance in a laboratory compared to a typical residential house. In this study, a 3-ton single-stage heat pump was initially tested in a two-story house located inside an environmental chamber with controllable ambient conditions. The same make and model of the heat pump was then tested in a psychrometric testing facility, employing the load-based testing method. The study aims to compare the cooling and heating mode performance and dynamic response between the house and laboratory tests, validate the virtual building modeling approach of the methodology, and determine load-based laboratory tests' effectiveness in capturing dynamic interactions between equipment and a residential house. The differences in coefficient of performance (COP) of the test unit between the two facilities were within 3 %, except for 9 % at 95°F (35 °C) and 5 % at 104°F (40 °C) outdoor temperature cooling dry-coil tests. The heat pump's cycling rate response, representing its dynamic response, matched well between the lab and house results. These findings demonstrate the effectiveness of the load-based testing methodology in capturing the dynamic performance of heat pumps in a laboratory setting. [ABSTRACT FROM AUTHOR]

In the blooming area of Internet technology, the concept of Internet-of-Things (IoT) holds a distinct position that interconnects a large number of smart objects. In the context of social IoT (SIoT), the argument of trust and reliability is evaluated in the presented work. The proposed framework is divided into two blocks, namely Verification Block (VB) and Evaluation Block (EB). VB defines various ontology-based relationships computed for the objects that reflect the security and trustworthiness of an accessed service. While, EB is used for the feedback analysis and proves to be a valuable step that computes and governs the success rate of the service. Support vector machine (SVM) is applied to categorise the trust-based evaluation. The security aspect of the proposed approach is comparatively evaluated for DDoS and malware attacks in terms of success rate, trustworthiness and execution time. The proposed secure ontology-based framework provides better performance compared with existing architectures. [ABSTRACT FROM AUTHOR]

This paper presents a novel radiant heating system with a wall-embedded micro heat pump (WEMHP) for residential buildings. The interior surface temperature of the exterior wall-section empowered by the micro heat pump is independently controlled, enabling distributed thermal comfort delivery. The micro heat pump consists of a miniature compressor along with an aluminum roll-bond condenser and evaporator. In contrast to conventional hydronic radiant systems and heat pumps with separate indoor and outdoor units (i.e., split systems), the WEMHP is a "packaged" system that would not require on-site installation and charging of a secondary water loop and circulation pump or refrigerant piping. This could ultimately lead to reduced installation and maintenance costs. In this study, a detailed system model is presented and integrated with a single-zone building model to assess the energy performance of the WEMHP in heating mode. For a designed living room scenario with an external wall WEMHP-to-wall ratio (HPWR) of 0.6 and window-to-wall ratio (WWR) of 0.2, the simulation results show that up to 23 % energy savings compared with a baseline air-to-air heat pump are possible. The results also indicate the HPWR needs to be higher than 0.4 to achieve performance comparable to the baseline. Additionally, experiments were conducted in a laboratory environment in which surface temperatures were controlled to emulate different scenarios for integration of WEMHP technology and to evaluate thermal comfort conditions. The experimental results show that the median operative temperature differences in the indoor environment were within 0.5 °C for various locations while the largest radiant asymmetry was 2.2 °C for the designed room configuration. Moreover, simulations were conducted to evaluate thermal comfort conditions in applications having a smaller HPWR of 0.4 with various values of WWR. Overall, the combined simulation and experimental study shows that the WEMHP has potential to reduce energy use while maintaining thermal comfort at acceptable levels where the HPWR is higher than 0.4. [ABSTRACT FROM AUTHOR]

Background: Coronavirus disease-2019 (COVID-19) is associated with thromboembolism. Antiphospholipid antibody (APLa) formation is one of the mechanisms. Vitamin D deficiency has been associated with thrombosis in antiphospholipid antibody syndrome. Objective: Measure APLa and vitamin D in hospitalized COVID-19 patients with and without thrombosis to evaluate if thromboembolism is associated with concomitant APLa and vitamin D deficiency. Methods: Case-control study. Hospitalized COVID-19 patients with a thromboembolic event (ischemic stroke, myocardial infarction, deep venous thrombosis/pulmonary embolism, Cases n = 20). Controls (n = 20): Age, sex-matched without thromboembolic events. Patients with autoimmune disorders, antiphospholipid antibody syndrome, thrombophilia, anticoagulation therapy, prior thromboembolism, chronic kidney disease 3b, 4, end-stage renal disease, and malignancy were excluded. Given the limited current literature on the role of concomitant antiphospholipid antibodies and vitamin D deficiency in causing venous and/or arterial thrombosis in hospitalized COVID-19 patients, we enrolled 20 patients in each arm. Anti-cardiolipin IgG/IgM, beta-2 glycoprotein-1 IgG/IgM, lupus anticoagulant and vitamin D levels were measured in both groups. Results: Cases were 5.7 times more likely to be vitamin D deficient (OR:5.7, 95% CI:1.3–25.6) and 7.4 times more likely to have any one APLa (OR:7.4, 95% CI: 1.6–49.5) while accounting for the effects of sex. Patients with both APLa and vitamin D deficiency had significantly more thrombosis compared to patients who were antibody positive without vitamin D deficiency (100% vs 47.4%; p = 0.01). Conclusions: Thrombosis in COVID-19 was associated with concomitant APLa and vitamin D deficiency. Future studies in COVID-19 should assess the role of vitamin D in reducing thrombosis. [ABSTRACT FROM AUTHOR]

Efficient electric heat pumps that replace fossil-fueled heating systems could significantly reduce greenhouse gas emissions. However, electric heat pumps can sharply increase electricity demand, causing high utility bills and stressing the power grid. Residential neighborhoods could see particularly high electricity demand during cold weather, when heat demand rises and heat pump efficiencies fall. This paper presents the development and field demonstration of a predictive control system for an air-to-air heat pump with backup electric resistance heat. The control system adjusts indoor temperature set-points based on weather forecasts, occupancy conditions, and data-driven models of the building and heating equipment. Field tests from January to March of 2023 in an occupied, all-electric, 208 m 2 detached single-family house in Indiana, USA, included outdoor temperatures as low as − 15 ° C. On average over these tests, the control system reduced daily heating energy use by 19% (95% confidence interval: 13%–24%), energy used for backup heat by 38%, and the frequency of using the highest stage (19 kW) of backup heat by 83%. Concurrent surveys of residents showed that the control system maintained satisfactory thermal comfort. The control system could reduce the house's total annual heating costs by about $300 (95% confidence interval: 23%–34%). These real-world results could strengthen the case for deploying predictive home heating control, bringing the technology one step closer to reducing emissions, utility bills, and power grid impacts at scale. • First field deployment of predictive control for an air-to-air heat pump in a cold climate. • Review of all known field studies of supervisory control for residential HVAC. • Reduced heating energy use by 13%–24% and use of highest-stage backup heat by 83%. • Occupants reported similar thermal comfort to benchmark control system. • Discussion of deployment labor, costs, challenges, and scalability. [ABSTRACT FROM AUTHOR]