Design and implementation of a fire-responsive cooling–suppression integrated system for mitigating fire risks in data-center GPU servers

Nowadays, high-rise buildings are developing very fast to cater to the increase in demand in major urban cities. This phenomenon has contributed to several environmental problems in both construction and operation. High-rise buildings design parameters seem to lack contextual environmental consideration. Evaluating the impact of such design parameters is a practical approach to enhance the overall energy and thermal performance. Existing research gaps are distinguished based on this review. Future research directions are also proposed through a methodological scheme to investigate comparatively, the effects of different geometric factors on both thermal and energy performance, specifically in the high-rise residential buildings with consideration to different climatic regions. Keywords: Energy Performance; Thermal Performance; High-rise Buildings; High-rise Residential BuildingseISSN: 2398-4287 © 2019. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia.DOI: https://doi.org/10.21834/e-bpj.v4i11.1717

Thermal and energy performance of green roof and cool roof: A comparison study in Shanghai area

Quantitative integration of fire risk with life cycle analysis of building: The case of thermal insulation

Author(s): Less, Brennan; Walker, Iain; Levinson, Ronnen | Abstract: In this literature review and analysis, we focus on the thermal, moisture and energy performance of sealed and insulated attics in California climates. Thermal. Sealed and insulated attics are expected to maintain attic air temperatures that are similar to those in the house within +/- 10°F. Thermal stress on the assembly, namely high shingle and sheathing temperatures, are of minimal concern. In the past, many sealed and insulated attics were constructed with insufficient insulation levels (~R-20) and with too much air leakage to outside, leading to poor thermal performance. To ensure high performance, sealed and insulated attics in new California homes should be insulated at levels at least equivalent to the flat ceiling requirements in the code, and attic envelopes and ducts should be airtight. We expect that duct systems in well-constructed sealed and insulated attics should have less than 2% HVAC system leakage to outside. Moisture. Moisture risk in sealed and insulated California attics will increase with colder climate regions and more humid outside air in marine zones. Risk is considered low in the hot-dry, highly populated regions of the state, where most new home construction occurs. Indoor humidity levels should be controlled by following code requirements for continuous whole-house ventilation and local exhaust. Pending development of further guidance, we recommend that the air impermeable insulation requirements of the International Residential Code (2012) be used, as they vary with IECC climate region and roof finish. Energy. Sealed and insulated attics provide energy benefits only if HVAC equipment is located in the attic volume, and the benefits depend strongly on the insulation and airtightness of the attic and ducts. Existing homes with leaky, uninsulated ducts in the attic should have major savings. When compared with modern, airtight duct systems in a vented attic, sealed and insulated attics in California may still provide substantial benefit. Energy performance is expected to be roughly equivalent between sealed and insulated attics and prescriptive advanced roof/attic options in Title 24 2016. System performance can also be expected to improve, such as pull down time, performance at peak load, etc. We expect benefits to be reduced for all advanced roof/attic approaches, relative to a traditional vented attic, as duct system leakage is reduced close to 0. The most recent assessments, comparing advanced roof/attic assemblies to code compliant vented attics suggest average 13% TDV energy savings, with substantial variation by climate zone (more savings in more extreme climates). Similar 6-11% reductions in seasonally adjusted HVAC duct thermal losses have been measured in a small subset of such California homes using the ducts in conditioned space approach. Given the limited nature of energy and moisture monitoring in sealed and insulated attic homes, there is crucial need for long-term data and advanced modeling of these approaches in the California new and existing home contexts.

Cleaner production of flame-retardant-glass reinforced epoxy resin composite for aviation and reducing smoke toxicity

Numerical prediction of thermal insulation performance and stress distribution of thermal barrier coatings coated on a turbine vane

Estimating thermal performance of thermosyphons by artificial neural networks

Thermal performance and thermal stress analysis of a supercritical CO2 solar conical receiver under different flow directions

Asymmetric microstructures are of particular interest to many technical fields. Such structures can produce anisotropic flow-fields, which, for example, can be used to control heat and mass transport processes. Anisotropic wicking structures can now be systematically engineered with unique micro-pillar geometries and spatial pillar-placement distributions. Such asymmetric wicking structure designs are of particular interest to the thermal management community due to need to cool heterogeneous materials with specific heat load configurations. In this study, asymmetric half-conical micropillars have been fabricated utilizing two-photon polymerization. Macroscopic characterization of anisotropic flow-field velocities is performed via high-speed videography. High-speed thin-film interferometry and microscopic side-angle videography are also used to characterize the microscale evolution of meniscus curvature during inter-pillar wicking. The wicking velocity is observed to be directly proportional to both the meniscus curvature and the cross-sectional area of the micro-pillars (normal to the flow). An anisotropic hemiwicking model is also described with comparisons to experimental data. The hemiwicking model predicts the macroscopic wicking behavior (within 20% or less) for the relatively broad range of pillar geometries and pillar spacing configurations. These anisotropic flow-field predictions can help engineers design the next-generation of micro-structured heat sinks, fluid-based sensors and chemical harvesting systems.

This research aims to support the choice of an appropriate dynamic louver shading system (DL-SS) within double-skin facade insulated glazed units (DSF-IGUs) as a high-performance integrated window system (DSF-IGUs/DL-SS) that meets both thermal and energy performance via daylight availability under a tropical climate. The research framework has developed a multi-objective optimization method to achieve research objectives via optimizing two different scenarios of the proposed system. The first scenario was optimized for daylighting availability, meanwhile, the second scenario was optimized for energy and thermal performance. For each scenario, the best solutions are selected from respective Pareto fronts according to energy efficiency criteria, thermal comfort via enhancing daylighting availability. Based on the best options resulting from both optimizations, the final step involved comparing the results of all performance indicators in the best cases to select the best solution. Overall, based on the optimizing objectives, the ranking of the best cases varied based on giving priority to the improvement objective in the optimization process. For each scenario, the best solutions are selected from the respective Pareto fronts. Overall, ranking of the best cases varied based on giving priority to the improvement objectives. Optimizing DL-SS within DSF-IGUs while giving priority to improving energy and thermal comfort while maintaining daylighting at acceptable levels is more reasonable. Thus, the DSF-IGUs/DL-SS best-case resulting from the second optimization scenario was overcome all best cases and ranked first in energy and thermal comfort. Compared to the base case, the differences of total Predicted mean vote and percentage of dissatisfied for better thermal comfort achieved were -0.35% and -1.48% with an average decreased by 22.99% and 28.72%, respectively. The differences of total energy and cooling load for better energy performance reduced by -96.84 kwh/m2. and -86.88 kwh with an average decreased by 25.33% and 26.20%, respectively. Meanwhile, the total satisfied of spatial Daylight Autonomy for better daylighting distribution and better daylighting availability of useful daylighting illuminance improvement were improved by -5.54% and +24.76% with an average percentage variation increased by 6.25% and 36.87%, respectively.

DOI: 10.7764/RDLC.17.3.499 As part of a thermal retrofitting process of existing housing, energy and thermal performance is normally predicted by dynamic simulation that supposes standardized patterns of building use, without considering the key role of the users in building's energy consumption. This represents a weakness in how the evaluation and design of retrofitting projects is structured, as integrally determining factors in thermal and energy performance are not considered. Integrated evaluations of the homes being improved will help to choose effective and objective guidelines. This work proposes a more objective and holistic evaluation that uses varied and compared techniques, involving the user in post-occupancy evaluation so that they provide feedback for the improvement's design. The integrated diagnosis comprises numerical calculations, onsite measurements, energy simulations and an estimation of the user's perception, with the goal of showing the different results obtained through the different methods. The study shows great differences in what users perceive and expect with the suggestions for thermal improvement obtained from the simulation. It is concluded that, to attain a higher user satisfaction and a better energy performance of the building, thermal improvement strategies must be defined not solely based on standards or previous cases but must consider the expectations of the inhabitants and including experimentally measured values of certain physical-construction properties to calibrate the dynamic simulations.

Case studies of energy consumption in residential buildings in Russia's middle belt area

Estimation of a building’s heating and cooling loads is an important factor taken into account implementation of energy saving measures in order to enhance energy performance of the building. In this work, the heating and cooling loads are predicted to enhance the building energy performance using different types of artificial neural networks namely, Elman network, recurrent network and back propagation network. The effect of eight input variables (relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, glazing area distribution) on two output variables (heating load and cooling load of residential buildings) is studied. The collected features are given as input to various neural networks for predicting the heating and cooling loads. The performance of the method is calculated in terms of mean absolute error, mean square error and mean relative error. Among all the networks back-propagation neural network has highest accuracy. The mean absolute error in predicting the loads is found to be 0.1 for heating load and 0.1254 for cooling load which is much better than already existing methods. The results of the work further reinforce the fact that ANN is an important tool for prediction and analysis of energy performance of a building.

Purpose Climate change reports from New Zealand claim that climate change will impact some cities such as Auckland from a heating-dominated to a cooling-dominated climate. The benefits and risks of climate change on buildings' thermal performance are still unknown. This paper examines the impacts of climate change on the energy performance of residential buildings in New Zealand and provides insight into changes in trends in energy consumption by quantifying the impacts of climate change. Design/methodology/approach The present paper used a downscaling method to generate weather data for three locations in New Zealand: Auckland, Wellington and Christchurch. The weather data sets were applied to the energy simulation of a residential case study as a reference building using a validated building energy analysis tool (EnergyPlus). Findings The result indicated that in Wellington and Christchurch, heating would be the major thermal load of residential buildings, while in Auckland, the main thermal load will change from heating to cooling in future years. The revised R-values for the building code will affect the pattern of dominant heating and cooling demands in buildings in Auckland in the future, while in Wellington and Christchurch, the heating load will be higher than the cooling load. Originality/value The findings of this study gave a broader insight into the risks and opportunities of climate change for the thermal performance of buildings. The results established the significance of considering climate change in energy performance analysis to inform the appropriate building codes for the design of residential buildings to avoid future costly changes to buildings.

Periodic inspection of false ceilings is mandatory to ensure building and human safety. Generally, false ceiling inspection includes identifying structural defects, degradation in Heating, Ventilation, and Air Conditioning (HVAC) systems, electrical wire damage, and pest infestation. Human-assisted false ceiling inspection is a laborious and risky task. This work presents a false ceiling deterioration detection and mapping framework using a deep-neural-network-based object detection algorithm and the teleoperated ‘Falcon’ robot. The object detection algorithm was trained with our custom false ceiling deterioration image dataset composed of four classes: structural defects (spalling, cracks, pitted surfaces, and water damage), degradation in HVAC systems (corrosion, molding, and pipe damage), electrical damage (frayed wires), and infestation (termites and rodents). The efficiency of the trained CNN algorithm and deterioration mapping was evaluated through various experiments and real-time field trials. The experimental results indicate that the deterioration detection and mapping results were accurate in a real false-ceiling environment and achieved an 89.53% detection accuracy.