An integrated pipeline for building performance analysis:Daylighting, energy, natural ventilation, and airborne contaminant dispersion

Early design decisions influence the performance of a building significantly. Yet, computational support for performance assessment during early design is very limited. This research proposes an analysis pipeline for the accurate and comprehensive assessment of building performance by integrating simulation-based analysis tools that perform daylighting, computational fluid dynamics, energy, and contaminant transport simulations, as well as wind tunnel testing that performs velocity and pressure measurements to generate wind pressure coefficients. The pipeline is implemented in three different ways: hybrid, model-based, and empirical workflows. The hybrid workflow combines computational fluid dynamics simulations and wind tunnel testing, while the model-based and empirical workflows utilize computational fluid dynamics simulations and wind tunnel testing, respectively. In the pipeline, computational fluid dynamics is used early on to evaluate a high number of alternatives, leading to the selection of a limited number of good-performing options. Following this, wind tunnel testing is used to “correct” the initial wind pressure coefficient results for increased accuracy. Therefore, a hybrid approach operating with high accuracy that can effectively explore the design search space is needed. The pipeline is tested on a hypothetical office building with different shading device configurations. The coupling of computational and physical testing methods in a hybrid workflow significantly enhanced the accuracy of airflow-related data, which is underestimated by 15.4% using the model-based workflow. Moreover, the hybrid workflow managed the complexity of the design search space by the assessment and elimination of different design alternatives by the stepwise simulation workflow. The inclusion of shading devices also improved the accuracy of airflow-related data. If the shading devices had not been modeled for the simulations and had not been tested, the results would have overestimated the ventilation rate by 85% and underestimated the ventilation rate by 1.4%, respectively. The study's contribution is significant as it proposes a pipeline for a more accurate and comprehensive assessment of building performance, which can inform design decisions and improve the overall building's performance.</p

Study of Toxic Gas Ingress in Non-Process Areas

Although the majority of incidents involving toxic gas release in process industries occur outdoors, nearby buildings and its indoor environments are also at high risk. Particularly, non-process areas such as administration buildings are often the least protected, even though they are in the vicinity of potential sources. In literature, indoor exposure modelling techniques range from simple statistical regression and mass balance approaches to more complex models such as multi-zone and computational fluid dynamics (CFD). Therefore, to study toxic gas infiltration, a proper selection of models is required. Despite the significant risk posed by such events in process facilities, there is still a lack of data and comparative studies concerning the appropriate models and mitigation methods. This work investigates a realistic pipeline leak in a natural gas facility and the subsequent H2S exposure of the nearby administration building. A comparative study is performed by utilizing a dispersion model (SLAB), a multi-zone model (CONTAM) and a CFD model (Quick Urban and Industrial Complex – QUIC). The influence of ventilation network, wind speed, direction, and pressure on toxic gas ingress is examined. Furthermore, the sensitivity of wind pressure calculation on the toxic gas infiltration rate by using American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) correlation and CFD modelling is studied. Indoor toxic levels are attained using combinations of the above mentioned models. Results on indoor toxic levels indicated high sensitivity to wind characteristics which led to varying risks and conclusions. A detailed description of different scenarios and findings is also presented

Optimization of dry storage for spent fuel from G.A. Siwabessy nuclear research reactor

© IJTech 2018. This study proposes a method of optimizing the dry storage design for nuclear-spent fuel from the G.A. Siwabessy research reactor at National Nuclear Energy Agency of Indonesia (BATAN). After several years in a spent fuel pool storage (wet storage), nuclear spent fuel is often moved to dry storage. Some advantages of dry storage compared with wet storage are that there is no generation of liquid waste, no need for a complex and expensive purification system, less corrosion concerns and that dry storage is easier to transport if in the future the storage needs to be sent to the another repository or to the final disposal. In both wet and dry storage, the decay heat of spent fuel must be cooled to a safe temperature to prevent cracking of the spent fuel cladding from where hazardous radioactive nuclides could be released and harm humans and the environment. Three optimization scenarios including the thermal safety single-objective, the economic single-objective and the multi-objective optimizations are obtained. The optimum values of temperature and cost for three optimization scenarios are 317.8K (44.7°C) and 11638.1 US$for the optimized single-objective thermal safety method, 337.1K (64.0°C) and 6345.2 US$ for the optimized single-objective cost method and 325.1K (52.0°C) and 8037.4 US$ for the optimized multi-objective method, respectively

VENTILATION IMPACT ON AIRBORNE TRANSMISSION OF RESPIRATORY ILLNESS IN STUDENT DORMITORIES

This work presents a study of the effect of ventilation rates on the bioaerosols that cause upper respiratory illness. A network of 147 sensors was placed in a pair of dormitories on a college campus to measure carbon dioxide concentrations over two semesters. The concentration results served as input into multi-zone ventilation models of the two buildings, which had different heating, ventilation, and air conditioning (HVAC) systems. The dormitory with a central mechanical ventilation system had, as expected, a higher turnover of fresh air compared to the other, which relied on exhaust fans and infiltration. This well-ventilated building also contained far fewer occupants with recorded upper respiratory illness incidence in comparison to the poorly ventilated building. The central ventilation system increased dorm room ventilation rates by 500%, while decreasing respiratory illness incidence by over 85%. Comparative studies have shown similar findings with increased ventilation reducing incidence of upper respiratory illness by an order of magnitude

Controlling Hazardous Releases While Protecting Passengers in Civil Infrastructure Systems

The threat of accidental or deliberate toxic chemicals released into public spaces is a significant concern to public safety, and the real-time detection and mitigation of such hazardous contaminants has the potential to minimize harm and save lives. Furthermore, the safe evacuation of occupants during such a catastrophe is of utmost importance. This research entails a comprehensive means to address such scenarios, through both the sensing and control of contaminants, and the modeling of and potential communication to occupants as they evacuate. First, a computational fluid dynamics model has been developed that is capable of detecting and mitigating the hazardous contaminant over several time horizons using model predictive control optimization. Next, an evacuation agent-based model has been designed and coupled with the flow control model to simulate agents evacuating while interacting with a dynamic, threatening environment. Finally, a physical prototype (blower wind tunnel) has been constructed with capability of detection (via Ethernet-connected camera) of and mitigation (via compressed-air operated actuators) of a `contaminant' (i.e. smoke) to test the real-time feasibility of the computational fluid dynamics flow control model.PHDEnvironmental EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/135812/1/srimer_1.pd

Green Design Studio: A modular-based approach for high-performance building design

Building energy and indoor air quality (IAQ) are of great importance to climate change and people’s health and wellbeing. They also play a key role in mitigating the risk of transmissions of infectious diseases such as COVID-19. Building design with high performance in energy efficiency and IAQ improvement can save energy, reduce carbon emissions, and improve human health. High-performance building (HPB) design at the early design stage is critical to building’s real performance during operation. Fast and reliable prediction of building performance is, therefore, required for HPB design during the early design iterations. A modular-based method to analyze building performance on energy efficiency, thermal comfort, IAQ, health impacts, and infection risks was developed, implemented, and demonstrated in this study. The modular approach groups the building technologies and systems to modules that can be analyzed at multi-scale building environments, from urban scale, to building, room, and personal scale. The proposed approach was implemented as a plugin on Rhino Grasshopper, a 3D architectural geometry modeling tool. The design and simulation platform was named Green Design Studio. Reduced-order physics-based models were used to simulate thermal, air, and mass transfer and storage in the buildings. Three cases were used as the study case to demonstrate the module-based approach and develop the simulation platform. Optimization algorithms were applied to optimize the design and settings of the building modules beyond the reference case. The case study shows that the optimal design of the small office determined by the developed platform can save up to 27.8% energy use while mitigating more than 99% infection risk compared to the reference case. It reveals that the optimization of green building design using the proposed approach has high potential of energy saving and IAQ improvement. In support of the application of the Green Design Studio platform, a database of green building technology modules for energy efficiency and IAQ improvement was created. Two selected emerging IAQ strategies were studied using the proposed approach and the developed tool, including the in-duct needlepoint bipolar ionizer and the combination of displacement ventilation and partitions. The in-duct ionization system can provide an equivalent single pass removal efficiency (SPRE) of 3.8-13.6% on particle removal without significant ozone and volatile organic compounds (VOCs) removal and generation with minimal energy use. The combined application of displacement ventilation and desk partitions can also effectively mitigate potential virus transmission through coughing or talking. The abundant performance data from experiments and detailed simulations for the studied technologies will be used by the database of the green building technologies and systems. It will allow these two technologies to be applied through the Green Design Studio approach during the early-design stage for a high-performance building. This can potentially help to address IAQ issues, particularly the airborne transmission of respiratory diseases, while maintaining high energy efficiency

Assessment of infection probability indices for airborne diseases in confined spaces: combination of CFD and analytical modelling

The paper presents a framework for probabilistic assessment of likelihood of infection from airborne diseases in confined spaces which are continuously occupied for relatively long periods (e.g., school classrooms). The proposed approach is based on a combination of computational fluid dynamics (CFD) pre-calculations and analytical post-processing, to define relevant indices of infection probability. The practical applicability of the method is demonstrated through a case study, where different ventilation scenarios are considered for a school classroom. Corresponding infection probability indices are determined globally for the group of occupants. Furthermore, since the method does not rely on the well-mixing assumption, local probability indices are determined for each occupied location. The obtained results confirm the intuition that an increase of ventilation and/or air filtration reduces the overall likelihood of infection, though the observed positive effect is not uniform within the space. The presented methodology can also be considered as complementary to simpler approaches