Evaluating the performance of passive chilled beams with respect to energy efficiency and thermal comfort

Existing modeling approaches for passive chilled beams determined from tests on individual chilled beams in a laboratory are not adequate for assessing overall energy usage and occupant comfort within building simulation programs. In addition, design guidelines for passive chilled beam systems are needed for identifying appropriate applications and optimal configurations. This thesis includes (i) extensive experimental studies for characterizing the performance of passive chilled beams, in both laboratory settings and in field studies, (ii) development of passive chilled beam performance prediction models, (iii) integration of these models into building simulation models/tools and (iv) use of building simulation for overall assessment of different passive chilled beam system configurations in different climates in order to provide guidelines for appropriate applications. Experiments were conducted with a single passive chilled beam in a laboratory setting and with multiple passive chilled beams installed in a real occupied office space. Based on the experimental results, models that can predict total cooling capacity and chilled surface temperature of passive chilled beams were developed. These models use essential operating conditions of the system and thermal conditions in the environment as inputs and are able to predict the energy and thermal comfort performances of the passive chilled beam system when integrated into a system simulation. The validity of using a model developed from laboratory tests on a single passive chilled beam in a system simulation for spaces with multiple chilled beams was evaluated. Comparison of laboratory and field measurements indicates that the conventional method of predicting total cooling capacity of a passive chilled beam from laboratory measurements underestimates its performance when installed in a system. These differences could have an important impact on system sizing and commissioning. Side-by-side field measurements were conducted to compare energy and comfort performance of a passive chilled beam system against constant and variable air volume systems for nearly identical office spaces. While maintaining very similar thermal comfort levels in the two offices, the passive chilled beam system led to a 57% reduction in electric energy compared to the constant air volume system. However, the variable air volume (VAV) system consumed 21% less energy compared to the passive chilled beam system during the field measurements. This is mostly because of the current configuration of the passive chilled beam system which represents the worst case scenario in terms of system configuration. The parallel air system used in the field measurement is a typical air system including the outdoor air and return air damper system. As a starting point followed by various configurations assessment with computer simulations, the return air damper was closed during the entire field measurements of the passive chilled beam system. In order to consider more realistic energy savings compared to VAV systems, alternative passive chilled beam configurations were evaluated using a system simulation model that was validated with the available measurements. The integrated simulation tool was developed and validated for the case study office space and was then used to perform comprehensive comparisons of alternative passive chilled beam and conventional systems in order to evaluate savings potential in various climatic zones. While maintaining the same thermal environments in spaces, the best passive chilled beam configuration provided electrical energy savings up to 24% for hot and humid climates and up to 35% savings for hot and dry climates compared to a variable air volume system. The radiation cooling effects of passive chilled beams were also analyzed through experiments and simulations. Both experiments and computer simulations revealed that the effect of the radiation cooling of passive chilled beams is not significant in terms of energy savings and thermal comfort improvement. Based on simulation results covering various passive chilled beam system configurations and climatic zones, the percentage of radiation cooling energy relative to total passive chilled beam cooling energy varied between 7 to 15

Energy Savings Potential of Passive Chilled Beam System as a Retrofit Option for Commercial Buildings in Different Climates

This study considers a cooling system retrofit for a commercial building in different climates by introducing a passive chilled beam system. A typical single duct VAV system, widely used in large office buildings, was considered as a baseline scenario; a combination of the air system and passive chilled beams was considered as a retrofit scenario. The retrofit with minimum modifications in this study includes installations of (1) multiple passive chilled beam units, (2) additional pumps and a closed water loop for the passive chilled beam units and (3) a heat exchanger where the chilled beam’s water loop exchanges heat with the return side of the chilled water loop. The results showed total energy savings up to 22% for climates where the sensible load is much higher than the latent load

Common Faults and Their Prioritization in Small Commercial Buildings

This study documents faults that are commonly found in small commercial buildings based on a literature review and discussions with building commissioning experts. It also provides a list of prioritized faults based on an estimation of the prevalence, energy impact, and financial impact of each fault. A total of 39 faults were analyzed for this paper and classified by location, stage, and type. The technical complexity of detecting each type of fault based on typically available information was evaluated for each fault. The annual energy impact (AEI) and annual financial impact (AFI) of each fault were estimated based on available information. Based on these estimates, 20 top priority faults were identified. Seven out of the 20 top priority faults occur in vapor compression systems such as air-conditioning, heat pump, and refrigeration equipment. Nonstandard charging, condenser, and evaporator fouling are the most important faults for this type of equipment

Performance Evaluation of a Passive Chilled Beam System and Comparison with a Conventional Air System

This study compares the performance of a system employing passive chilled beams with a conventional air system in a typical open plan office setting. Both energy efficiency and thermal comfort are taken into account as performance indicators. A typical single duct variable air volume system, widely used in large office buildings, was considered as a conventional system; a combination of the air system and passive chilled beams was considered as a typical passive chilled beam system. Measurements from full-scale experiments conducted in open plan offices (Living Labs of the Center for High Performance Buildings at Purdue) are used to develop a data-driven passive chilled beam model that can predict the total cooling capacity as well as surface temperatures under different operating conditions. In simulating the performance of the two systems, the same operative temperature was used in order to have a fair comparison. Additionally, the effect of radiation cooling of the passive chilled beam was investigated. The overall results showed about maximum 10-21% total electrical energy savings (5-23% reduction in chiller and 55% reduction in supply fan electrical energy) and thermal comfort improvement of 0.3-0.4 on a PMVscale (12-15% on a PPD scale) associated with the passive chilled beam system, depending on the system configuration. The radiation cooling of the passive chilled beam is not significant, since the effective surface area for radiant exchange with the room is much less than the surface area for convective heat transfer and temperature differences are relatively low.

End-to-End Learnable Multi-Scale Feature Compression for VCM

The proliferation of deep learning-based machine vision applications has given rise to a new type of compression, so called video coding for machine (VCM). VCM differs from traditional video coding in that it is optimized for machine vision performance instead of human visual quality. In the feature compression track of MPEG-VCM, multi-scale features extracted from images are subject to compression. Recent feature compression works have demonstrated that the versatile video coding (VVC) standard-based approach can achieve a BD-rate reduction of up to 96% against MPEG-VCM feature anchor. However, it is still sub-optimal as VVC was not designed for extracted features but for natural images. Moreover, the high encoding complexity of VVC makes it difficult to design a lightweight encoder without sacrificing performance. To address these challenges, we propose a novel multi-scale feature compression method that enables both the end-to-end optimization on the extracted features and the design of lightweight encoders. The proposed model combines a learnable compressor with a multi-scale feature fusion network so that the redundancy in the multi-scale features is effectively removed. Instead of simply cascading the fusion network and the compression network, we integrate the fusion and encoding processes in an interleaved way. Our model first encodes a larger-scale feature to obtain a latent representation and then fuses the latent with a smaller-scale feature. This process is successively performed until the smallest-scale feature is fused and then the encoded latent at the final stage is entropy-coded for transmission. The results show that our model outperforms previous approaches by at least 52% BD-rate reduction and has $\times5$ to $\times27$ times less encoding time for object detection. It is noteworthy that our model can attain near-lossless task performance with only 0.002-0.003% of the uncompressed feature data size.Comment: Under peer review for IEEE TCSV

Identification and Characterization of mRNA and lncRNA Expression Profiles in Age-Related Hearing Loss

Objectives Age-related hearing loss (ARHL), or presbycusis, is caused by disorders of sensory hair cells and auditory neurons. Many studies have suggested that the accumulation of mitochondrial DNA damage, the production of reactive oxygen species, noise, inflammation, and decreased antioxidant function are associated with subsequent cochlear senescence in response to aging stress. Long non-coding RNA (lncRNA) has been reported to play important roles in various diseases. However, the function of lncRNA in ARHL remains unclear. In this study, we analyzed the common expression profiles of messenger RNA (mRNA) and lncRNA through ARHL-related RNA-sequencing datasets. Methods We selected and downloaded three different sets of RNA-sequencing data for ARHL. We performed differential expression analysis to find common mRNA and lncRNA profiles in the cochleae of aged mice compared to young mice. Gene Ontology (GO) analysis was used for functional exploration. Real-time quantitative reverse-transcription polymerase chain reaction (qRT-PCR) was performed to validate mRNAs and lncRNAs. In addition, we performed trans target prediction analysis with differentially expressed mRNAs and lncRNAs to understand the function of these mRNAs and lncRNAs in ARHL. Results We identified 112 common mRNAs and 10 common lncRNAs in the cochleae of aged mice compared to young mice. GO analysis showed that the 112 upregulated mRNAs were enriched in the defense response pathway. When we performed qRT-PCR with 1 mM H2O2-treated House Ear Institute-Organ of Corti 1 (HEI-OC1) cells, the qRT-PCR results were consistent with the RNA-sequencing analysis data. lncRNA-mRNA networks were constructed using the 10 common lncRNAs and 112 common mRNAs in ARHL. Conclusion Our study provides a comprehensive understanding of the common mRNA and lncRNA expression profiles in ARHL. Knowledge of ARHL-associated mRNAs and lncRNAs could be useful for better understanding ARHL and these mRNAs and lncRNAs might be a potential therapeutic target for preventing ARHL

End-Use Load Profiles for the U.S. Building Stock: Market Needs, Use Cases, and Data Gaps

States and utilities are developing increasingly ambitious energy goals. Part of the solution to meeting these goals is improving electric grid flexibility. This includes shifting electric demand to align with grid needs. Thus, identifying and using building energy efficiency and other distributed energy resources to produce the highest grid value requires highly resolved, accurate and accessible electricity end-use load profiles (EULPs). EULPs quantify how and when energy is used. Currently, few accurate and accessible end-use load profiles are available for utilities, public utility commissions, state energy offices and other stakeholders to use to prioritize investment and value energy efficiency, demand response, distributed generation and energy storage. High-quality EULPs are also critical for determining the time-sensitive value of efficiency and other distributed energy resources, and the widespread adoption of grid-interactive efficient buildings (GEBs).For example, EULPs can be used to accurately forecast energy savings in buildings or identify energy activities that can be shifted to different times of the day. This report serves as the first-year deliverable for a multiyear U.S. Department of Energy-funded project, End-Use Load Profiles for the U.S. Building Stock, that intends to produce a set of highly resolved EULPs of the U.S. residential and commercial building stock. The project team, made up of researchers from the National Renewable Energy Laboratory (NREL), Lawrence Berkeley National Laboratory (LBNL), and Argonne National Laboratory, ultimately will use calibrated physics-based building energy models to create these EULPs

Thermochromic Metal Halide Perovskite Windows with Ideal Transition Temperatures

Urban centers across the globe are responsible for a significant fraction of energy consumption and CO2 emission. As urban centers continue to grow, the popularity of glass as cladding material in urban buildings is an alarming trend. Dynamic windows reduce heating and cooling loads in buildings by passive heating in cold seasons and mitigating solar heat gain in hot seasons. In this work, we develop a mesoscopic building energy model that demonstrates reduced building energy consumption when thermochromic windows are employed. Savings are realized across eight disparate climate zones of the United States. We use the model to determine the ideal critical transition temperature of 20 to 27.5 {\deg}C for thermochromic windows based on metal halide perovskite materials. Ideal transition temperatures are realized experimentally in composite metal halide perovskite film composed of perovskite crystals and an adjacent reservoir phase. The transition temperature is controlled by co-intercalating methanol, instead of water, with methylammonium iodide and tailoring the hydrogen-bonding chemistry of the reservoir phase. Thermochromic windows based on metal halide perovskites represent a clear opportunity to mitigate the effects of energy-hungry buildings

Safety and Efficacy of Second-Generation Everolimus-Eluting Xience V Stents Versus Zotarolimus-Eluting Resolute Stents in Real-World Practice Patient-Related and Stent-Related Outcomes From the Multicenter Prospective EXCELLENT and RESOLUTE-Korea Registries

ObjectivesThis study sought to compare the safety and efficacy of the Xience V/Promus everolimus-eluting stent (EES) (Abbott Vascular, Temecula, California) with the Endeavor Resolute zotarolimus-eluting stent (ZES-R) (Medtronic Cardiovascular, Santa Rosa, California) in “all-comer” cohorts.BackgroundOnly 2 randomized controlled trials have compared these stents.MethodsThe EXCELLENT (Efficacy of Xience/Promus Versus Cypher to Reduce Late Loss After Stenting) and RESOLUTE-Korea registries prospectively enrolled 3,056 patients treated with the EES and 1,998 patients treated with the ZES-R, respectively, without exclusions. Stent-related composite outcomes (target lesion failure [TLF]) and patient-related composite outcomes were compared in crude and propensity score-matched analyses.ResultsOf 5,054 patients, 3,830 (75.8%) had off-label indication (2,217 treated with EES and 1,613 treated with ZES-R). The stent-related outcome (82 [2.7%] vs. 58 [2.9%], p = 0.662) and the patient-related outcome (225 [7.4%] vs. 153 [7.7%], p = 0.702) did not differ between EES and ZES-R, respectively, at 1 year, which was corroborated by similar results from the propensity score-matched cohort. The rate of definite or probable stent thrombosis (18 [0.6%] vs. 7 [0.4%], p = 0.306) also was similar. In multivariate analysis, off-label indication was the strongest predictor of TLF (adjusted hazard ratio: 2.882; 95% confidence interval: 1.226 to 6.779; p = 0.015).ConclusionsIn this robust real-world registry with unrestricted use of EES and ZES-R, both stents showed comparable safety and efficacy at 1-year follow-up. Overall incidences of TLF and definite stent thrombosis were low, even in the patients with off-label indication, suggesting excellent safety and efficacy of both types of second-generation drug-eluting stents

Representing Small Commercial Building Faults in EnergyPlus, Part I: Model Development

Small commercial buildings (those with less than approximately 1000 m2 of total floor area) often do not have access to cost-effective automated fault detection and diagnosis (AFDD) tools for maintaining efficient building operations. AFDD tools based on machine-learning algorithms hold promise for lowering cost barriers for AFDD in small commercial buildings; however, such algorithms require access to high-quality training data that is often difficult to obtain. To fill the gap in this research area, this study covers the development (Part I) and validation (Part II) of fault models that can be used with the building energy modeling software EnergyPlus® and OpenStudio® to generate a cost-effective training data set for developing AFDD algorithms. Part I (this paper) presents a library of fault models, including detailed descriptions of each fault model structure and their implementation with EnergyPlus. This paper also discusses a case study of training data set generation, representing an actual building