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At least 325 records · Page 18

Risk-based System Upgrade Planning for AOT-IC Presentation [Slides]

The number of deployed systems and different HW/SW form factors makes it difficult to maintain a complete understanding of their health which leads to a reduced level of certainty when assessing risk and trying to prioritize system upgrade efforts. AOT-IC must constantly plan and execute system upgrade and replacement projects to ensure the longevity of the control system. There are many more projects needed than the group can realistically accomplish given schedule and resource constraints. The group must prioritize their upgrade projects to choose only the highest priority projects to execute each year. Currently plans upgrade and replacement projects based on alignment with mission needs, group vision, resource availability, and qualitative risk assessments based on SME estimates. The group maintains a risk register. This is useful as a tool for shaping strategic planning but currently lacks the quantitative data and process needed to generate accurate risk assessments.

43 PARTICLE ACCELERATORS↗

Risk Model for EM Decision Support Toolsets

The Government Office of Accountability (GAO) has published several reports identifying the need for the Department of Energy (DOE) Office of Environmental Management (EM) to address mounting costs for DoE's cleanup program. DOEEM could greatly benefit from independent decision tool-sets/models that would allow them to evaluate options and inform business decision at the enterprise level considering site-specific life cycle costs and system plans. Program goals: Develop a tool-set that enables EM to independently evaluate alternatives, assess outcomes from different contracting strategies, and inform critical decisions for the enterprise. Project goals: Adaption of a Risk Model for integration with complimentary tool-sets for project level decision making. Operational Events: Discrete event model that evaluates operational variables (e.g. capacity, throughput, maintenance constraints) and identify bottlenecks. Identifying and Bounding Project Risk: Identify risks that impact confidence in meeting goals (e.g. production). Life cycle Cost: Evaluate impacts of staffing levels, inventory, and capital investments on life cycle costs. Methods and approach: Monte Carlo Analysis is being executed to generate results: Input derives from Risk Register Data; Tied to Projected and Target Schedules; Incorporates float duration within the model. Assumes associated risk mitigation actions being completed within a timeline of five fiscal years. Metrics include: Confidence in Meeting Production Goal; Confidence in Safety Standards; Confidence in Continuous Operation; Other Metrics can be added as appropriate regarding specific site needs. The adapted risk model can be used as a stand alone decision tool or can be integrated complementary tool-sets (i.e. process and cost models) for project-specific decisions. These support tool-sets can then be integrated with others for site- and complex- level evaluations. Future work includes designing an adaptable and modular framework that would allow integration of multiple tool-sets for holistic and/or targeted evaluation of alternative strategies for decision making that could lead to risk and cost reduction across the enterprise.

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Infrastructure and DFLAW Support at Hanford - 20443

Manhattan Project era infrastructure systems are degrading at an accelerated pace across the Department of Energy's (DOE) Environmental Management complex. Revitalizing, rejuvenating and right-sizing these systems to ensure reliability for ongoing cleanup missions is a major focus at the 580-square- mile Hanford Site in southeast Washington State. The push to complete construction, commissioning, startup, and operation of facilities and systems in the Direct-Feed Low-Activity Waste (DFLAW) program at Hanford by 2023 requires considerable coordination among site contractors and a significant investment in infrastructure. The passage of time also poses a challenge. It has been about 75 years since facilities were first operated at the site, and approximately 40 years of plutonium production created a legacy of unidentified active and abandoned underground obstacles and waste sites that must be avoided when building and upgrading the infrastructure. Converting infrastructure systems originally built to support plutonium production from the 1940's to the 1980's and upgrading those systems to optimize technology is an ever-changing balance of funding profiles, available resources and execution strategies. The DOE Richland Operations Office (RL) has long recognized the need for increased investment in Hanford Site infrastructure to support the future processing of approximately 56 million gallons of waste currently stored in large underground tanks. When DFLAW is fully operational, safe and reliable infrastructure systems will be needed to ensure continuity of operations around the clock, 365 days a year. These include roadways, water, power, sewer, information technology systems and facilities. To ensure the readiness of Hanford's infrastructure to support treating tank waste in the next three years, 15 projects were identified with a combined value of $133.8 million. Through calendar year 2019, 7 infrastructure projects have been substantially completed and the remaining 8 projects, with a remaining value of $103.8 million, are scheduled to be completed by December 2023. RL and its site services/infrastructure contractor, Mission Support Alliance (MSA), regularly evaluate the needs of the DFLAW program and other Hanford Site missions to ensure the highest priority systems are addressed. In addition to a fast-approaching deadline for round-the-clock treatment operations, RL and MSA face another significant infrastructure challenge. As cleanup is being completed in a 220-square-mile area called the River Corridor, most of the cleanup operations going forward will occur in a 20-square-mile area in the center of the Hanford Site, known as the Central Plateau. Infrastructure systems are becoming more congested in an already overcrowded area. This paper/presentation will outline some of the challenges Hanford faces while executing infrastructure reliability projects. (authors)

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Evaluation of Autonomous Vehicle Sensing and Compute Load on a Chassis Dynamometer

The sensing and compute load auxiliary energy consumption in autonomous vehicles may be significant due to the large number of sensors and the high compute load from sensor processing and route planning. To understand this issue, this study investigates the top-down energy usage of an electric 2015 Kia Soul fully instrumented with state sensors and a state-specific computer for path planning and sensor processing. A chassis dynamometer was then used to evaluate the cases of (1) no sensors or computation, (2) only sensors operating, and (3) sensors plus compute load. The vehicle was operated autonomously on the dynamometer using a PolySync drive-kit with drive-by-wire longitudinal control. The DynoJet model 224xLC was used to adapt the eddy current dynamometer's road load parameters to comply with an Environmental Protection Agency drive schedule and to evaluate performance against the Argonne National Laboratory Digital Dynamometer Dataset. On the UDDS-HWFET combined driving cycle, the stock battery's range was reduced by 5.6% for sensors alone and 12.2% for sensors and compute load. These results show that the added sensing and compute auxiliary load from automated and autonomous systems is significant and that research efforts need to be spent investigating new energy efficient systems.

Brown, Nicholas E.↗

GlideinBenchmark: collecting resource information to optimize provisioning

Choosing the right resource can speed up job completion, better utilize the available hardware, and visibly reduce costs, especially when renting computers in the cloud. This was demonstrated in earlier studies on HEPCloud. However, the benchmarking of the resources proved to be a laborious and time-consuming process. This paper presents GlideinBenchmark, a new Web application leveraging the pilot infrastructure of GlideinWMS to benchmark resources, and it shows how to use the data collected and published by GlideinBenchmark to automate the optimal selection of resources. An experiment can select the benchmark or the set of benchmarks that most closely evaluate the performance of its workflows. GlideinBenchmark, with the help of the GlideinWMS Factory, controls the benchmark execution. Finally, a scheduler like HEPCloud's Decision Engine can use the results to optimize resource provisioning.

Mambelli, Marco [Fermilab] (ORCID:0000000294892681↗

A computationally efficient algorithm for computing convex hull prices

Electricity markets worldwide allow participants to bid non-convex production offers. While non-convex offers can more accurately reflect a resource's capabilities, they create challenges for market clearing processes. For example, system operators may be required to execute side payments to participants whose costs are not covered through energy sales as determined via traditional locational marginal pricing schemes. Convex hull pricing minimizes this and other types of side payments while providing uniform (i.e., locationally and temporally consistent) prices. Computing convex hull prices involves solving either a large-scale linear program or the Lagrangian dual of the corresponding non-convex scheduling problem. Further, the former approach requires explicit descriptions of market participants' convex hulls. While linear programs for computing convex hull prices are large, their structure is naturally decomposable by generators. Here, in this work, we propose and empirically analyze a Benders decomposition approach to computing convex hull prices that leverages recent advances in convex hull formulations for thermal generating units. We demonstrate across a large set of test instances that our decomposition approach only requires modest computational effort, obtaining solutions at least an order of magnitude faster than the equivalent large-scale linear programming approach. Overall, we provide a computationally feasible method for computing convex hull prices for industrial scale market clearing problems, enabling the possibility of practical adoption of this advanced pricing mechanism.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

EJFAT: Towards Intelligent Compute Destination Load Balancing

To handle increased data flow, Jefferson Lab (JLab) is partnering with ESnet for development of an AI/ML directed compute work Load Balancer (LB) of UDP streamed data. The LB is FPGA based featuring dynamically configurable, low latency and high throughput destination address switching. The LB provides integration of edge and core computing to support JLab experimental programs, the Electron-Ion Collider, as well as data centers of the future. In the ESnet/JLab FPGA Accelerated Transport (EJFAT) initiative, the function of the LB Data Plane (DP) is to redirect data streams to selectable (but unknown to sender) destination hosts based on current worload and within that host to destination ports as a function of sub- stream id. This effects hierarchical scaling, first across compute machines for processing over a series of events and second, across ports so different data source sub-streams may be assigned to different processors for further parallelization. The LB Control Plane (CP) programs the DP using compute farm telemetry to direct and balance workloads across a compute cluster as the operating conditions require. While Proportional/Integrative/Derivative (PID) controllers are often seen in similar applications, here we investigate the feasibility of a Reinforcement Learning (RL) based schedule manager running in the CP to provide dynamic updates to the DP scheduling policy.

Lawrence, David↗

GlideinBenchmark: collecting resource information to optimize provisioning

Choosing the right resource can speedup jobs completion, better utilize the available hardware and visibly reduce costs, especially when renting computers on the cloud. This was demonstrated in earlier studies on HEPCloud. But the benchmarking of the resources proved to be a laborious and time-consuming process. This paper presents GlideinBenchmark, a new Web application leveraging the pilot infrastructure of GlideinWMS to benchmark resources, and shows how to use the data collected and published by GlideinBenchmark to automate the optimal selection of resources. An experiment can select the benchmark or the set of benchmarks that most closely evaluate the performance of its workflows. With GlideinBenchmark and the help of the GldieinWMS Factory it controls the benchmark execution. Finally, a scheduler like HEPCloud’s Decision Engine can use the results to optimize resource provisioning.

Mambelli, Marco↗

Illuminating gut microbiome signaling pathways that regulate host circadian rhythms

The gut microbiome affects host physiology by modulating nutrient acquisition and creating chemical signals that are received by host receptors. The molecular details of the orchestration of these microbial signaling processes remain largely unclear. We used a function-centric approach to interrogate the mechanistic links between gut microbiome metabolism and host circadian rhythms. We used rodent models, including germ-free mice, to determine how the gut microbiome influences host chronobiology by assaying metabolites in the gut and in circulation, and we used activity-based protein profiling to provide direct functional links to individual taxa. We specifically investigated how externally imposed behavioral schedules, such as feeding schedules, can desynchronize biological rhythms in metabolic organs (e.g., the gut, pancreas, and liver) from the central circadian rhythms regulated by the brain. We hypothesize that the gut microbiome creates chemical signals that can be entrained by feeding/fasting schedule to induce internal metabolic misalignment. Elaborating on the findings of this project will elucidate the chemical signals from the microbiome that modulate biological rhythms in the host’s metabolic organs.

59 BASIC BIOLOGICAL SCIENCES↗

Compiling Quantum Circuits for Dynamically Field-Programmable Neutral Atoms Array Processors

Dynamically field-programmable qubit arrays (DPQA) have recently emerged as a promising platform for quantum information processing. In DPQA, atomic qubits are selectively loaded into arrays of optical traps that can be reconfigured during the computation itself. Leveraging qubit transport and parallel, entangling quantum operations, different pairs of qubits, even those initially far away, can be entangled at different stages of the quantum program execution. Such reconfigurability and non-local connectivity present new challenges for compilation, especially in the layout synthesis step which places and routes the qubits and schedules the gates. In this paper, we consider a DPQA architecture that contains multiple arrays and supports 2D array movements, representing cutting-edge experimental platforms. Within this architecture, we discretize the state space and formulate layout synthesis as a satisfiability modulo theories problem, which can be solved by existing solvers optimally in terms of circuit depth. For a set of benchmark circuits generated by random graphs with complex connectivities, our compiler OLSQ-DPQA reduces the number of two-qubit entangling gates on small problem instances by 1.7x compared to optimal compilation results on a fixed planar architecture. To further improve scalability and practicality of the method, we introduce a greedy heuristic inspired by the iterative peeling approach in classical integrated circuit routing. Using a hybrid approach that combined the greedy and optimal methods, we demonstrate that our DPQA-based compiled circuits feature reduced scaling overhead compared to a grid fixed architecture, resulting in 5.1X less two-qubit gates for 90 qubit quantum circuits. These methods enable programmable, complex quantum circuits with neutral atom quantum computers, as well as informing both future compilers and future hardware choices.

Physics↗

Generic and ML Workloads in an HPC Datacenter: Node Energy, Job Failures, and Node-Job Analysis

HPC datacenters offer a backbone to the modern digital society. Increasingly, they run Machine Learning (ML) jobs next to generic, compute-intensive workloads, supporting science, business, and other decision-making processes. However, understanding how ML jobs impact the operation of HPC datacenters, relative to generic jobs, remains desirable but understudied. In this work, we leverage long-term operational data, collected from a national-scale production HPC datacenter, and statistically compare how ML and generic jobs can impact the performance, failures, resource utilization, and energy consumption of HPC datacenters. Our study provides key insights, e.g., ML-related power usage causes GPU nodes to run into temperature limitations, median/mean runtime and failure rates are higher for ML jobs than for generic jobs, both ML and generic jobs exhibit highly variable arrival processes and resource demands, significant amounts of energy are spent on unsuccessfully terminating jobs, and concurrent jobs tend to terminate in the same state. We open-source our cleaned-up data traces on Zenodo (https://doi. org/10.5281/zenodo.13685426), and provide our analysis toolkit as software hosted on GitHub (https://github.com/atlarge-research/2024-icpads-hpc-workload-characterization). This study offers multiple benefits for data center administrators, who can improve operational efficiency, and for researchers, who can further improve system designs, scheduling techniques, etc.

crossanalysis↗

Fracture Network Prediction Using Physics-based Machine Learning Algorithms

In recent years, systematic CO2 injection into geological reservoirs across the U.S. has gained traction as a strategy to mitigate greenhouse gas emissions. This approach necessitates precise monitoring to ensure secure containment, minimize risks, and optimize storage management. Our study leverages machine learning (ML) techniques to advance the understanding of CO2 injection processes, focusing on the Illinois Basin. Over a three-year injection period, we analyzed microseismic data, identifying 19 temporal intervals with significant bottom-hole pressure changes. By partitioning microseismic events into these intervals and estimating b-values, we revealed over 100 clusters of events related to fracture initiation or reactivation. Advanced spatial analysis highlighted horizontally-oriented fractures along the NNW-SSE axis. This quantification of fracture networks informs dynamic injection scheduling, work-over strategies, and risk assessments, enhancing carbon capture, utilization, and storage (CCUS) operations. Additionally, our methodology offers valuable insights for oil and gas operations and geothermal development, supporting fracture-based monitoring and risk mitigation.

Kumar, Abhash↗

The Wonders of Physics -- Public Outreach (Final Technical Report)

The mission of The Wonders of Physics (TWoP) outreach program is to generate interest in physics among people of all ages and backgrounds. The objective is to generate interest in physics, increase appreciation for the significance of physics in our lives, and encourage children to consider careers in science and plasma physics. The primary means for achieving that objective is to make entertaining presentations to audiences that would not normally be motivated to attend a lecture on physics or plasmas, while at the same time introducing some of the fundamental concepts and applications. During this reporting period, the students Michael Hall, Megan Tabbutt and Connor Sullivan, Director of Communications Sarah Perdue, Director of Undergraduate Program Jim Reardon, and Senior Information Processing Consultant Paul Wilhite worked to make outreach programs a success and prepare for the future of The Wonders of Physics, which will continue. Because of the curtailment of public events due to Covid-19, there will not be an in person Annual Show or Physics Fair in 2021, but a video competition has already been announced and planning continues for The Wonders of Physics in 2022 and beyond. The annual shows and Physics Fair are scheduled for February 12-13 and February 19-20, 2022. These continue to be our premier outreach events, engaging diverse audiences in real hands-on science. Further shows and exploration stations are planned.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

PHOENIX Electrostatic Design

PHOENIX (Portable, High-efficiency, Optimal ENergy Imaging X-rays) is a quasi-DC, electrostatic, vacuum-diode designed as a portable x-ray source with national defense and commercial applications. The patent-pending PHOENIX concept combines a megavoltage, Cockroft-Walton voltage multiplier with a Van de-Graaff electrostatic charge-storage dome to create a vacuum-diode suitable for x-ray production. Naturally this structure must minimize internal electric fields to reduce electrical breakdown while simultaneously reducing size and weight to enhance portability. In this paper we describe the optimization process and model results obtained using the COMSOL multi-physics code. We describe three models: a prototype model built to demonstrate the PHOENIX concept as part of Laboratory Directed Research and Development (LDRD) Mission Foundation Research (MFR) Phase-I , a “back-of-the-envelope” design used as a starting point for further COMSOL optimization, and finally, the optimized geometry implemented in the MFR Phase-II. In all cases compromises resulting from cost, schedule, and manufacturing constraints were taken into account as the design progressed.

42 ENGINEERING↗

Decommissioning of the V1 Nuclear Power Plant Jaslovske Bohunice - 20270

The paper focuses on introducing the approach and method applied for decommissioning of the V1 nuclear power plant (further the 'V1 NPP') located in Jaslovske Bohunice in the Slovak Republic, to the conference participants. The Paper outlines activities and steps necessary to comply with the requirements contained in the decision of the Slovak government from 1999 regarding the early shutdown of the V1 NPP. The company responsible for the V1 NPP decommissioning is Jadrova a vyradovacia spolocnost, a.s., (further JAVYS) with the State as a sole shareholder. On the basis of the V1 NPP Decommissioning Conceptual Plan, out of four assessed options, JAVYS selected the immediate decommissioning option (the 'IDO') for the V1 NPP. On the basis of multi-criteria analysis, the IDO specified the approach of immediate and continuous dismantling of equipment followed by demolition of buildings and preparation of the site for its further potential use. The IDO also included the summary of technical, environmental, legislative information as well as the determination of assumed costs for decommissioning of the V1 NPP. Prior to commencement of the V1 NPP decommissioning, within the process of termination of operation, activities connected with de-fuelling, monitoring, processing of historical waste and, not to forget, the process of obtaining the license for the V1 NPP decommissioning were executed. JAVYS decided to divide the decommissioning process into two stages. In 2011, JAVYS obtained a license for the first stage of the V1 NPP decommissioning. Within this stage, dismantling of inactive equipment, demolitions of inactive buildings, monitoring of systems and preparatory works for the upcoming stage of decommissioning were implemented. In 2015, in line with the license for the 2. stage of the V1 NPP decommissioning, the activities of decontamination and dismantling of contaminated and active equipment as well as demolitions of remaining buildings began. In this stage radioactive waste (RAW) produced during the decommissioning is to be processed. After decontamination, the material fulfilling the free release criteria is to be released into the environment, the site is to be cleared from the scope of the Atomic Act and released from the surveillance of the national regulators. Future application of certain methods and techniques for decontamination and dismantling in similar environments might bring an added value to the operators. Paper includes a description of best practices for Nuclear Power Plant VVER type reactors decommissioning. Schedule comparison is given to show how the critical path of certain projects is being managed. Application of the International Standard for Decommissioning Costing (ISDC) methodology provides a uniform method which enables comparison of cost estimates to other nuclear facilities under decommissioning. The cost estimate for the V1 NPP decommissioning has been continuously updated based on more advanced and detailed information on the decommissioning activities and projects. Monitoring of progress of the V1 NPP decommissioning is performed via four key-performance indicators. The Earned Value Management (EVM) methodology is used for evaluating time and cost aspect of decommissioning activities while waste conditioning index is calculated by comparing the actually produced waste to planned values of waste for a respective monitored period. Radiological safety index is assessed by comparison of the personnel records on the individual yearly doses received by each respective employee to the boundary value. (authors)

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MODULARITY-AT-SCALE FOR COST COMPETITIVE DEPLOYMENT OF NUCLEAR ENERGY

Modularity options have been limited for traditional nuclear energy deployment due to the conventional light water reactor (LWR) safety requirements, such as high pressure retaining heavy and robust containment structures. However, a relatively new regulatory approach called ‘Functional Containment’ has potential to allow less expensive and more flexible designs for non LWRs. Functional containment provides flexibility in design and deployment based on risk informed and performance-based criteria, so that reactors are not over-designed. Non-nuclear industry has successfully used modular design approaches in automotive, aerospace, chemical processing, building construction, and ship building. These industries have shown that modular construction reduces construction time by around 30% - 50% compared to the conventional stick built approach. The nuclear industry can use similar approaches to reduce construction time and costs, balanced with safety requirements, using the functional containment approach. This paper discussing the background of modularity in nuclear energy, examples of less learned, modularity approaches in non-nuclear industries and the potential of cost and schedule savings through the emerging regulatory design flexibilities potentially enabling combination of modular deployment at different scales.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Modularity-at-scale for advanced reactors presentation

Modularity options have been limited for traditional nuclear energy deployment due to the conventional light water reactor (LWR) safety requirements, such as high pressure retaining heavy and robust containment structures. However, a relatively new regulatory approach called ‘Functional Containment’ has potential to allow less expensive and more flexible designs for non-LWRs. Functional containment provides flexibility in design and deployment based on risk-informed and performance-based criteria, so that reactors are not over-designed. Non-nuclear industry has successfully used modular design approaches in automotive, aerospace, chemical processing, building construction, and ship building. These industries have shown that modular construction reduces construction time by around 30% - 50% compared to the conventional stick-built approach. The nuclear industry can use similar approaches to reduce construction time and costs, balanced with safety requirements, using the functional containment approach. This paper discussing the background of modularity in nuclear energy, examples of less learned, modularity approaches in non-nuclear industries and the potential of cost and schedule savings through the emerging regulatory design flexibilities potentially enabling combination of modular deployment at different scales.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Survey of Multizone Airflow Simulation Software

H-Canyon simulates the building and process ventilation to ensure positive contamination control for any modifications as well as evaluating off-normal conditions. Simulations can also be used to identify air quality of personnel occupied areas. The models can be classified into two groups, single and multi-zone models. As the name states, a single zone model assumes that the building can be described by a single, well-mixed zone. Whereas large buildings have structures that must be described as multizone. Multizone airflow models deal with the difficulty of flows in a building by distinguishing the effects of internal flow restrictions. Several models have been developed that take internal partitions into account. CONTAM (currently used) is a multizone airflow program created by NIST to determine airflows including infiltration, exfiltration, wind pressures acting outside the building, buoyancy effects caused by the indoor and outdoor air temperature difference. COMIS is a multizone air infiltration, ventilation, and contaminant transport model that was developed at Lawrence Berkeley National Laboratory. COMIS deals with applied pressure distribution, airflow components, HVAC systems, schedules, and contaminant transport. EnergyPlus is designed by DOE. It supports flexible component level configuration of HVAC models and simulates sub-hourly time steps to control fast dynamic systems. The program features include providing accurate environmental performance data including energy consumption and carbon emissions, and reporting solar gains on surfaces. Heavent is used to model industrial ventilation systems to control airborne contaminants. It's designed based on the American Conference of Governmental Industrial Hygienists (ACGIH) Ventilation manual. DesignBuilder is the most recognized and advanced user interface to EnergyPlus. It gives access to all of the most frequently required simulation capabilities covering building fabric, thermal mass, glazing, shading renewables, and HVAC analysis. The objective of this study is to identify all relevant software available including commercially licensed, freely licensed, and open source, that can be used to simulate large, complex process facility ventilation systems. All discovered software tools are evaluated for salient features and compared to the software tool currently used to simulate the H-Canyon ventilation system. The design criteria of a ventilation system has two basic requirements: Supplying fresh air for the occupants and changing the air in the room sufficiently; therefore, the smells, fumes, and contaminants will be removed. In this study, first, whether the software simulates airflow (infiltration, natural ventilation, and interzonal) or considers them to be inputs is discussed. Second, if indoor contaminant levels are considered; and finally suggestions on how airflow analysis can be more appropriately accounted for when performing airflow simulation of a building. All of the airflow software reviewed for this study can account for constant infiltration and natural ventilation rates that are not affected by changes in indoor and outdoor conditions. Modelling infiltration in EnergyPlus or DesignBuilder are applicable for small buildings and not appropriate for larger buildings like the H-Canyon. The effect of wind on external pressures, infiltration, and natural and mechanical ventilation, can also be calculated using all of these software. These programs have control options to switch between natural to mechanical ventilation modes or both (hybrid). Interzonal airflow can be applied which means one zone can be specified to receive a fixed amount of air from another zone. The following ventilation modeling software is recommended for further testing: CONTAM, COMIS, Heavent. The next step in evaluating the software will consist of creating test facility simulations using evaluation copies of the software.

42 ENGINEERING↗