This study develops a unified analytical framework for transient one-dimensional heat conduction in a source-free, constant-property solid slab subjected to a prescribed heat flux at one boundary and convection at the opposite boundary, with an extension to a prescribed variable slab thickness. For the fixed-thickness baseline problem, exact dimensional and nondimensional solutions are derived through steady-transient decomposition and eigenfunction expansion under mixed boundary conditions. The nondimensional formulation reveals the governing roles of the Fourier and Biot numbers and reconstructs the dimensional temperature field exactly.Two variable-thickness extensions are then established. The first is a reduced-order frozen-geometry formulation that treats thickness evolution through interval-wise updates and consistent remapping between successive slab states. The second is an exact moving-boundary formulation obtained by transforming the governing equation from the evolving physical domain to a fixed computational coordinate. The fixed-thickness slab is recovered exactly as a limiting case when the thickness remains constant.Validation against the steady-state limit confirms exact recovery of the classical conduction-convection series thermal-resistance model. Illustrative studies verify dimensional-nondimensional consistency, demonstrate the thermal effect of prescribed thickness variation, and compare the reduced-order and exact moving-boundary formulations. In the nondimensional sensitivity analysis, increasing the Biot number from 0.02 to 10 decreases the steady nondimensional heated-wall response from 51 to 1.1 (about 97.8%) and the steady nondimensional fluid-solid-interface response from 50 to 0.1 (about 99.8%), while the normalized conductive temperature drop across the slab remains unchanged. The resulting framework provides a physically interpretable benchmark and a rapid analytical tool for variable-thickness thermal analysis.

In this article, the impact of low air volume fraction air-induced pressure losses in vertical pipes was studied experimentally in a recirculated hydronic system. The test loop is 0.8 m tall with a uniform inner pipe diameter of 19 mm. The maximum total air volume fraction in the test loop was 8.6%. The local average air volume fractions in the pipes with vertical upward and downward flow were measured using the differential pressure method. Two sources of extra pressure loss caused by air in the pipes with vertical flow were identified: (1) frictional pressure loss caused by phase slip between air and water flow; and (2) the density difference between the upward and downward flows. Our measurements show that the combined incremental pressure loss caused by air at 6.8% total air volume fraction at a flow velocity of 0.6 m/s can be four times as high as the single-phase flow pipe frictional pressure loss at the same flow velocity in vertical pipe sections. At a flow velocity of 0.6 m/s, the density-induced pressure loss is approximately seven times the air frictional pressure loss at the same flow velocity.

A commonly budget and time constrained yet crucial measurement and verification process for chiller energy efficiency measures often requires rarely trended chiller performance data for the pre-retrofit or post-retrofit chiller necessitating chiller modeling for year-round performance prediction. This study evaluates chiller inverse modeling methods for measurement and verification applications. Variable speed drive-controlled centrifugal chillers operating in a hot and humid climate are used as case studies. Two scenarios are explored: one where full-range metered chiller data are available and another with limited data that requires a short-term metering process. The biquadratic black-box and Gordon-Ng with a variable entropy term models perform exceptionally well when full-range chiller performance data is available, displaying a coefficient of variation of approximately 5 % for both training and test datasets. However, in situations that use short-term metered data not covering the full range, the fundamental and Foliaco reformulated Gordon-Ng models outperform other models. These models show minimal degradation in average statistical performance when trained with onemonth metering data instead of four-month data, indicating their potential to capture the year-round chiller performance variation with short-term metered data. Furthermore, the optimal metering period for an accurate modeling process is identified as one containing data from at least one shoulder month like April, May, or October for a hot and humid climate. These findings provide valuable guidance for practitioners involved in chiller efficiency measure assessments, emphasizing the significance of proper model selection and an appropriate metering period for a reliable measurement and verification process.

Closed-loop hydronic systems, widely used in heating and cooling applications, are essential for energy-efficient building operations. However, air entrainment significantly degrades their pumping efficiency, making it critical to understand the mechanisms behind air entrainment and its impact on system performance. This study investigates the origins of air entrainment and quantifies associated efficiency losses using a validated experimental model. Controlled experiments were designed to reveal the operational dynamics of air entrainment in closed-loop hydronic systems. Key findings identify three critical factors- air compression at the system's top, gravitational head reduction, and frictional pressure loss- that contribute to static pressure changes, driving water volume variations and subsequent air entrainment. Additionally, air entrainment was observed to alter system flow rates by shifting the system and pump curves, leading to measurable performance degradation. Results from a small test loop show that increasing the total air volume fraction from 0 % to 8.6 % reduces pumping efficiency by 40 %, with power inputs ranging from 27 W to 21 W. The experimental results align with the theoretical model, achieving an R2 value of 0.95. These findings underscore the importance of addressing air entrainment in hydronic systems and provide actionable insights for optimizing operational strategies, improving energy efficiency, and extending the reliability and service life of these systems in building applications.

This paper explores the minimum energy that would be required to provide all energy-using services currently used the U.S. office building sector if they were all provided by thermodynamically ideal devices that do not violate physical law. Data from the U.S. DOE and the General Services Administration were used to identify office building workspace services, equipment, occupancy and schedules. Internal building loads were estimated after identifying or conservatively approximating the thermodynamically ideal power required for each service. The average thermodynamically ideal office building in the U.S. would use 2.2 kWh/m2-yr or less, which represents 1.0% of the current average end-use consumption in the sector. Such a large gap between the thermodynamic limit and today's practice is related to the fact that the energy performance of all the internal gain producing equipment in buildings is far from ideal along with the HVAC equipment and envelope components. Ideal office buildings would use 69.7% of their energy for cooking and related domestic water heating and cooling; illumination accounts for a smaller portion, consuming 17.5%, while office equipment and cooling would use 6.9% and 5.9% of the total consumption, respectively. Dramatic reductions come from the elimination of heating energy and air distribution energy brought about by ideal adiabatic building envelopes and frictionless air distribution. Cooling energy is virtually eliminated by the combination of greatly reduced cooling loads and ideal Carnot equipment. But the thermodynamically ideal office equipment would use two orders of magnitude less energy than today as well.

This chapter emphasizes commissioning applied to existing buildings, but also provides commissioning guidance for the energy managers who are involved in construction projects. It provides energy managers with the information needed to decide whether to conduct an in-house commissioning program or to select and work with an outside commissioning provider. The commissioning process for existing buildings is described in detail, and common commissioning measures for existing buildings are described so the energy manager can choose how to implement a commissioning program. A detailed plan should be developed for ongoing commissioning activities to ensure that the improved performance is maintained as discussed in this chapter. The commissioning process has been described using an outside provider. Commissioning an existing building is a key energy management activity, often resulting in energy savings of 10%, 20% or sometimes 30% without substantial capital investment.

This paper introduces a multi-mode perturbation model for non-spherical bubbles, developed using potential function theory and spherical harmonics. Employing a sophisticated numerical framework that integrates adaptive time advancement (ATA) and mesh refinement (AMR), the study rigorously solves coupled ordinary differential equations (ODEs) and partial differential equations (PDEs) in a non-dimensional framework. Analysis is split between Rayleigh collapse under constant external pressure and dynamic collapse influenced by acoustic pressure waves. The study systematically investigates the effects of initial particle size, perturbation amplitude, and mode degree on Rayleigh collapse dynamics, revealing that larger bubbles exhibit longer collapse and rebound times, while smaller bubbles rapidly reach equilibrium. In scenarios involving acoustic waves, the investigation focuses on the impact of wave frequency and medium compressibility. Results indicate that higher wave frequencies and fluid compressibility significantly reduce the time for system oscillations to synchronize with external pressure waves, enhancing damping effects. Specifically, compressibility was found to accelerate synchronization, reducing large-amplitude oscillation cycles more than twofold compared to incompressible conditions. Additionally, at higher perturbation modes, amplitude damping occurs more rapidly, underscoring the influence of mode degree on the damping characteristics. Spanning Reynolds numbers from 1.65 to 1.65E+7 for Rayleigh collapses and 9.98E-4 to 9.98E+3 for acoustic-driven scenarios, the research highlights the substantial impact of fluid compressibility and perturbation parameters on bubble dynamics, providing insights that contrast sharply between micro-scale and macro-scale particle behaviors.

Chiller fault detection and diagnosis can optimize building energy and maintenance costs. Previous reviews have largely overlooked the detailed assessment of chiller fault detection methods; this study focuses on chiller methods proposed since 2004. Categorized into regression-based, classification-based, and knowledge-based approaches, the study delves into their procedural aspects and practical implications for field-installed chillers such as availability of the required training parameters and information, accuracy versus energy performance fault impact, and complexity of required data. Classification-based methods are mostly supervised learning, and few have been validated with faulty chiller data from real-world installations. Over 90% of classification-based, over 70% of regression-based, and all knowledge-based surveyed methods were tested using experimental data only. Some measured parameters like the subcooling temperature, oil feed pressure, and oil sump temperature that are commonly used in model training for detection and diagnosis algorithms are rarely measured in field installations. Despite significant research efforts to enhance the early detection of refrigerant leakage and condenser fouling faults, studies indicate minimal impact of these faults at low severities. Justifying their early detection may primarily rely on environmental considerations. To bolster field implementation, incorporating common factory-installed sensor parameters in new method development or testing of existing ones is recommended. Means that can provide faulty data for classification-based methods should also be devised. Hybrid methods that incorporate experts’ knowledge in the detection and diagnosis algorithms are encouraged and more testing of existing methods with real-world installations to ensure applicability is recommended.

This study investigates the dynamic response of deformable particles to pressure perturbations, utilizing analytical and numerical analyses. Numerical simulations using Fluent software explore the impact of internal pressure deviations, step changes, and oscillations in ambient pressure across a wide size range. The study uncovers systematic and damped oscillatory responses to pressure deviations, highlighting the significance of liquid viscosity and surface tension in determining equilibrium states. Particle size emerges as a key factor, influencing equilibrium pressures, dynamic responses, and power spectral characteristics. Findings include smaller particles exhibiting higher equilibrium pressures and longer stabilization times. Power Spectral Density (PSD) analysis reveals a consistent dominant frequency, with smaller particles displaying higher peak frequencies. Analytical exploration emphasizes the roles of surface tension, viscosity, temperature, and mean ambient pressure in shaping peak frequency and deformation magnitude. The analysis shows smaller particle size have larger peak frequency, but smaller deformation. Moreover, raising surface tension leads to a wider range of particle sizes whose peak frequencies are not zero.

Depletion of fossil fuel reservoirs, greenhouse gas emissions' impact on global warming, and rising energy costs are pushing the data center sector to reduce energy use. This paper reviews strategies for improving the energy performance of air-cooled systems in datacom facilities and enhancing temperature and flow distribution in white space by analyzing different airflow delivery architectures (hard floor and raised floor designs), eliminating cold and hot air mixing by incorporating cold/hot aisle containment or exhaust chimneys, and potential energy savings achievable by utilizing evaporative cooling systems. It was found that the optimal ventilation system is hard-floor architecture with locally-ducted supply and return air. Hard floor is less complicated than raised floor design, and overhead supply air can minimize hot spots at the top of racks. Airflow management strategies including cold and hot aisle formation, aisle containment, and exhaust chimneys can reduce annual cooling energy usage by 10-50% in conjunction with air-side and water-side economizers, minimize hot spots, and enhance thermal performance during cooling system failure. Hot-Aisle Containment or exhaust chimneys provide better thermal and energy performance than open and/or cold-aisle containment, but they require new ducting in traditional data centers. Depending on the climate and geographical location, evaporative cooling can reduce annual cooling energy usage by 20-70% and lead to Power Usage Effectiveness as low as 1.06. Evaporative coolers are more suitable for dry climates, but this limitation can be ameliorated by incorporating desiccant wheels and thermal energy storage.

Over the last decade, the demand for data center and network services has increased dramatically. To meet this demand, global average rack power density has risen from 2.4 kW/rack in 2011 to 8.4 kW/rack in 2020 with the aid of technological advancements. About 36% of global data centers have racks above 30 kW/rack. Average Power Usage Effectiveness (PUE) dropped from 2.5 in 2007 to 1.65 in 2013, but has been almost flat since then, at 1.59 in 2020. The depletion of finite fossil fuel reservoirs, adverse impact of greenhouse gas emissions on global warming, recyclability of electronic waste, and the rising cost of energy are pushing the datacom industry toward more energy-efficient and sustainable technologies including renewable energy, highly efficient elec-tronics cooling, waste heat recovery, passive cooling systems, and energy storage, which are broadly reviewed in this paper. Use of renewable energy resources through power purchase agreements rose by 346% from 2.4 GW in 2017 to 10.7 GW in 2020. Air-side economizers can reduce PUE by 30-50% and water-side economizers by 10-30%. The server/rack outlet is an ideal spot for waste heat recovery and can be coupled with a multi-stage heat pump to save significant energy if coupled to a district heating system. Active and passive deployment of thermal energy storage can save more than 20% of cooling energy and reduce temperature fluctuations by more than 60%. Edge computing, decentralization, and virtualization can lead to lower latency, higher scalability, and reliability during failure.

A simplified methodology was developed to determine the economically optimum plant configuration for a district heating and cooling system using low-grade geothermal fluids from depleted hydrocarbon wells. To accomplish this: center dot The optimum geothermal fluid flow rate and temperature supplied to the surface end-use system were determined. center dot The absorption chiller and the desiccant dehumidification and geothermal district heating systems were modeled for cooling, dehumidification, and heating, and simplified with relationships between the required geothermal fluid temperature and its output at different outside air conditions. center dot The surface end-use system modeling was developed by combining these heat-operated system models with load profiles of typical buildings. center dot The inlet temperature requirements and the maximum temperature drops of each system were studied, and possible system arrangements were investigated using the bin method. center dot Both the site energy load to energy ratio (LER) and the cost LER were introduced and calculated. When building loads are large and the integrated system operates at full capacity, the optimal arrangement is for the desiccant dehumidification and geothermal district heating systems to operate in parallel. The system was evaluated for a case study site where the yearly total energy output is 8572 MMBtu (9044 GJ), with a total LER of 14.08-23.76 (i.e., it requires 14-24 times fewer electric Btu than the energy output.) When the integrated system matches the building loads well, the optimized arrangement uses the absorption chiller system and the geothermal district heating system in parallel and in series with the desiccant dehumidification system. Its yearly total energy output is 3264 MMBtu (3444 GJ) with a cooling LER of 4.72-7.89 and a heating LER of 4.25-7.24. For all the integrated geothermal systems described above, the operating energy use would be less than one-fourth that of a traditional heating and cooling plant meeting the same loads for the case study site. Additional sites should be evaluated to determine the broader application of the methodology and the use of geothermal energy from depleted hydrocarbon wells.

Building cooling load consumption is heavily influenced by two factors, i.e., spatial correlations such as outside air conditions and temporal relations, which factors the occupancy influence into account. Moreover, the anomalies in cooling consumption patterns are mainly caused by the abnormal behavior of the time-dependency of such temporal networks. A novel framework for building cooling load prediction is proposed to explore these dependencies separately using regression and recurrent neural networks for spatial and temporal relations, respectively, and then combine their outputs using an ensemble approach. The proposed forecasting model provides a 3-4% higher R-2 value and 2-3% better CVRMSE accuracy when compared with the traditional machine learning model.

This research studies the estimation of peak electric demand savings on a community college campus and compares it with actual utility data for the purpose of accurately modeling the peak electric demand behavior. An internally-developed energy modeling program based on the ASHRAE Simplified Energy Analysis Procedure was used in this analysis. The peak demand of the campus was examined before and after the implementation of the existing building commissioning (EBCx) project, and it was found that an average of 34% peak demand savings were realized. The modeling framework used in this research was capable of accurately simulating the monthly peak demand savings.

This paper investigates the independent impact of several different existing building commissioning (EBCx) measures on peak electric demand, to help understand measures to prioritize based on peak demand savings along with the usually-assessed energy consumption savings. The investigation involves developing separate EnergyPlusT models for each EBCx measure, and comparing the peak electric demand generated by each model with a baseline model. The pre-EBCx and post-EBCx models are based on a community college campus which underwent an EBCx project between 2014 and 2015, resulting in an average of 34% savings in energy consumption and peak demand. The total peak demand reduction determined from the individual EBCx measures was only 26% compared to the measured reduction of 34%. Applying an outside air temperature reset schedule to AHUs' supply air temperature (SAT) setpoints reduced peak demand by an average of 16.7%, mainly due to the reduction of unnecessary cooling and reheating, especially in winter. The optimization of AHU control schedules, which minimized the unnecessary operation of some units during peak hours produced peak demand savings of 6%, while the optimization of space temperature setpoints contributed another 3%. While other measures impact electric demand during non-peak hours, none produced peak electric demand reduction greater than 1%. Other measures did not generate peak demand savings while still generating energy consumption savings, mainly for the reason of not having an impact during peak hours.

A good model fit is the central pillar of building energy consumption baseline modeling. Energy analysts often must undertake the arduous and tedious task of separating measured energy consumption data into groups reflecting a building's multiple operation modes. While a building sometimes has more than a weekday/weekend shift, a detailed operation schedule may not be easily available or accurate. If not treated carefully, operational idiosyncrasies can limit the performance of the baseline model. So far, the data separation methods deployed in published articles are either too simple to be effective for complex schedules or so intricate that many working in the field may find them inconvenient to implement. The proposed procedure in this study instead adopts a novel approach that automatically and comprehensively examines all data separation possibilities with pre-defined elementary day-types through a series of lack-of-fit F-tests. It then suggests a best one that balances model accuracy and simplicity. This procedure was tested on measured energy consumption data of 76 buildings and found to weigh simplicity more heavily than traditional statistical complexity-penalising metrics. It improved the CV-RMSE by 7.6 percentage points on average and helped extract information from the data to understand better the buildings' energy consumption patterns.

In warm and humid climates, a primary source of building energy consumption is dehumidification of conditioned air supplied to the building spaces. The system analyzed utilizes a selective membrane to remove water vapor from ambient air instead of a vapor compression cycle or a desiccant. This work analyzed a membrane dehumidification system with a focus on the system energy performance. A system performance goal was set by the project sponsor for an inlet air condition of 32.2 degrees C and 90% relative humidity, an outlet condition of 12.8 degrees C and 50% relative humidity and a total cooling load of 3.52 kW resulting in a target COP latent for the system of 3.34. Models of the basic system components were used to develop the system, analyze operating parameters and predict performance. The results indicate that the system requires two optimizations to meet the target performance: condenser pressure optimization and the use of multiple membrane segments operating at different pressures. Subsequently, a model was developed to analyze the performance of the final system configuration under a variety of operating conditions and yielded a maximum COP latent of 4.37 for membrane properties comparable to those of the earliest membrane module tested. This may be compared with a COP of about 3.5 for current refrigeration technology at these conditions. The best small membrane sample produced to date would increase the COP latent of the membrane system to well above 8, suggesting that the membrane system has high promise. Uncertainty analysis was also performed to assess the simulation results. (C) 2021 Elsevier Ltd and IIR. All rights reserved.

This study presents the energy savings impact of the Continuous Commissioning® (CC®) version of the Existing Building Commissioning (EBCx) process in 197 projects (592 buildings) since the inception of the process in the early 1990s. These are the results of a comprehensive evaluation of the impact of EBCx projects. The evaluation of the impact of EBCx by building type included 316 education buildings, 141 health care facilities, 13 laboratory facilities, 32 office buildings, as well as 90 miscellaneous facilities. The annual energy cost savings, as of December 2016, exceeded $29.7 million (2017 $), for 197 EBCx projects (over 59 million ft2 (5.48 million m2) of area). The median annual cost savings were $0.24/ft2 ($2.26/m2) for individual education buildings, $0.40/ft2 ($4.31/m2) for individual health care facilities, $1.54/ft2 ($16.58/m2) for individual laboratory facilities, $0.59/ft2 ($6.35/m2) for individual office buildings, $0.50/ft2 ($5.38/m2) for individual miscellaneous facilities. The median percent savings for electricity were up to 14%, the demand savings up to 14%, the natural gas savings up to 33%, the CHW savings ranged from 21 to 36%, and the HW savings ranged from 28 to 71%. The median percent savings are remarkably consistent by building type.