Use of discrete event simulation in hospital capacity planning

In recent years, the healthcare industry is undergoing a rapid expansion in the United States. For healthcare facilities, resource planning at early design stage is a critical step before architectural design. The ‘resources' here refer to both long term resources (pods, rooms, beds, configuration of one pod) in terms of capacity and configuration, and short term resources(staffs, equipments) in terms of capacity and allocation. To achieve performance targets defined by the clients, such as staff/equipment/bed utilization efficiency, average waiting time of all patients, turn away rate, an assessment and verification at the preliminary planning stage is necessary. There are at least two methods to solve this problem. The first is analytical in nature, relying on queuing theory, and falls under the industrial engineering field. The other is computational in nature, relying on process simulation, and specifically discrete event simulation. While queuing theory is easier to conduct, usually requiring less data, and providing more generic rules than simulation, simulation methods result in detailed information about patient flow modeling and deliver more accurate results. This paper is divided into three parts. The first part introduces queuing theory and discrete event simulation in terms of their principles, features and applications in healthcare planning. This is followed by a case study in the ED using discrete event simulation to plan pod configuration and number of pods for an emergency department. During this process, the simulation tool is introduced as an example instrument for advanced DES simulation. The paper ends with a discussion of outcomes. (1) DES is capable to differentiate between alternatives with small changes, and can be widely used to do capacity planning for healthcare facilities. (2) the chosen simulation tool supports the modelling and analysis steps well

Database Supported Bacnet Data Acquisition System for Building Energy Diagnostics

This paper reports a tool that can be used to acquire and store the BACnet (A Data Communication Protocol for Building Automation and Control Networks) data for the purpose of building energy system Fault Detection and Diagnostics (FDD). Building Automation Control (BAC) systems have become a common practice in recently constructed buildings in the United States. Although building operational data could readily be collected for various analysis purposes, there is still a debate in building community which or what FDD method is better in terms of performance matrix, such as false alarm rate and training data requirement, etc. Therefore, from the user's perspective, it is potentially beneficial to try out different FDD methods before the deployment, or even develop a dedicated FDD method in a specific case. This is the motivation for development of the BACnet data storage system discussed in this paper, which could then be used together with BACnet data acquisition module in an open source Building Control Virtual Test Bed (BCVTB) environment [2]. This paper discusses (1) Relational database schema development for the purpose of storing building operational data and FDD analysis data (2) Development of the connector in BCVTB that enables the transition from the BACnet module to the database module and (3)Testing of the integrated system in a real building. The relational database is intended to be general and detailed enough so that it can be applied to different buildings and projects with various complexity without any major structure change. The BACnet-reader to database connector enables seamless data flow from commercial BACnet system to user's customized workstation. The integrated system enables users to analyze building operational data in an effective and efficient way, which helps achieve automated FDD in buildings

Multi-criteria decision making under uncertainty in building performance assessment

Building performance assessment is complex, as it has to respond to multiple criteria. Objectives originating from the demands that are put on energy consumption, acoustical performance, thermal occupant comfort, indoor air quality and many other issues must all be reconciled. An assessment requires the use of predictive models that involve numerous design and physical parameters as their inputs. Since these input parameters, as well as the models that operate on them, are not precisely known, it is imprudent to assume deterministic values for them. A more realistic approach is to introduce ranges of uncertainty in the parameters themselves, or in their derivation, from underlying approximations. In so doing, it is recognized that the outcome of a performance assessment is influenced by many sources of uncertainty. As a consequence of this approach the design process is informed by assessment outcomes that produce probability distributions of a target measure instead of its deterministic value. In practice this may lead to a “well informed” analysis but not necessarily to a straightforward, cost effective and efficient design process. This paper discusses how design decision making can be based on uncertainty assessments. A case study is described focusing on a discrete decision that involves a choice between two HVAC system designs. Analytical hierarchy process (AHP) including uncertainty information is used to arrive at a rational decision. In this approach, key performance indicators such as energy efficiency, thermal comfort and others are ranked according to their importance and preferences. This process enables a clear group consensus based choice of one of the two options. The research presents a viable means of collaboratively ranking complex design options based on stakeholder’s preferences and considering the uncertainty involved in the designs. In so doing it provides important feedback to the design team

The impact of future climate scenarios on decision making in building performance simulation: a case study

Expected climate change may turn into a key challenge for building designers in the 21st century [Homes et al. 2007].In response to this challenge simulation packages have started to provide future climate scenarios to predict the energy demands and thermal comfort in buildings. The need to make predictions for climate change scenarios is becoming increasingly important.This paper describes the integration of climate change scenarios in one of the building performance simulation tools, i.e. VA114, which is used extensively in the Netherlands. Based on the existing traditional reference year "De Bilt 64/65", NEN 5060:2008 released a new norm that introduces four new climate files for different types of climate adjustments. KNMI on the other hand assembled four different future scenarios for the expected climate change. The climate files from the NEN and the KNMI future scenarios have been combined in a future climate data analysis for usage within the targeted simulation software VA114. The paper describes a case study focusing on the impact that a climate scenario may have on a concrete design decision. The case study involves two HVAC system designs: (1) a conventional cooling/heating system and (2) a heating/ cooling storage system. Both options are simulated and compared. The impact of climate change is shown on energy use and thermal comfort. It is then shown how the climate scenarios (and their inherent uncertainties) impact the uncertainty in the outcomes and how these outcomes influence the choice between the design options. The conclusions of the paper highlight the relevance of different (uncertain) climate scenarios and the role they play in design decision making

Analysis Methodology for Large Organizations' Investments in Energy Retrofit of Buildings

This paper presents a formal methodology that supports large organizations' investments in energy retrofit of buildings. The methodology is a scalable modeling approach based on normative models and Bayesian calibration. Normative models are a light- weight quasi-steady state energy models, which makes them scalable to large sets of buildings due to highly enhanced modeling efficiency. Then, Bayesian approach calibrates normative models such that calibrated models quantify uncertainty in the model while representing a building as operated. Calibrated models can further incorporate additional uncertainty from ECMs, and provide information about underperforming risks of ECMs. This paper illustrates the proposed retrofit analysis process through a case study, and demonstrates its feasibility to support large-scale retrofit decisions under uncertainty in the context of the ESCO industry

A GIS-based Energy Balance Modeling System for Urban Solar Buildings

AbstractSolar buildings as one type of decentralized renewable energy systems have been widely adopted to reduce carbon emissions. Related policy making faces two questions: how much total solar energy can be produced in a city and what proportion of building energy use can be supplied by the solar power? These questions remain hard to answer because of the lack of appropriate modeling systems, due to the data inconsistency and the limitation of current building energy and solar potential modeling methods in accounting for the urban context influences. This study tries to fill this gap by developing a GIS-based energy balance modeling system for urban solar buildings. This modeling system extends the system boundary from a single building to the urban building system, uses urban-scale data instead of costly survey, adopts widely used GIS-platform, and makes reasonable trade-offs between speed and accuracy. It consists of four major models: the Data Integration model, Urban Building Energy model, Urban Roof Solar Energy model and Energy Balance model. This modeling system is applied to Manhattan as a case study. The results show the spatial and temporal variations of building energy uses, the solar power potentials in the usable roof areas, and the self-supply and surplus ratio of buildings in Manhattan in 2012

A functional architecture for an e-Engineering hub

Many Information Technology (IT) tools now exist to support collaborative working between engineering organisations. These often address operational issues rather than tactical or strategic issues. In particular, there are no effective tools for collaborative project planning between project partners. An electronic engineering hub (e-Hub) is considered useful in this regard. This paper presents the functional architecture of the e- Hub – a major research result of the EU funded e-HUBs project (e-Engineering enabled by Holonomic and Universal Broker Services). The e-HUBs project developed a universal collaboration platform for engineering outsourcing with focus on supporting collaborative project planning process. The e-Hub offers an extended set of functions to engineering service providers (mostly small and medium-sized enterprises) such as application hosting and definition and development of collaborative engineering workflows. The paper discusses the theoretical background and the supporting technologies for the development of the functional architecture and presents the deployment of the engineering e-Hub prototype in a construction scenario

An evaluation of energy efficiency measures in a Turkish campus building for thermal comfort and economic risk

As new and retrofitted Turkish buildings adopt stateof-the-art energy efficiency measures, hidden risks associated with compromised thermal comfort and disappointing returns on investment could go unnoticed unless a building is subjected to an uncertainty and risk analysis. Standard deterministic predictions are not sufficient, as they do not capture the effects of uncertainty and variability with regard to local microclimate conditions, physical parameters, and discrepancies in the model formulations, also known as “model form uncertainties”. In this paper, we analyze the impact of uncertainty on the performance of a Turkish campus building. We examine the risk that an energy efficient design that is accepted because of the positive results of a conventional energy simulation, causes unacceptable discomfort and unsatisfactory returns on investment. The results of a comprehensive uncertainty analysis shows that these risks exist in certain areas and not in others. The predicted annual output of PV panels is relatively stable with only minor variability, which justifies the investment in Istanbul. Same with shading devices, which lead to a satisfactory internal rate of return under uncertainty. However, with regard to comfort we find that risks could be substantial. We find that relying completely on occupants opening and closing windows for fresh air with fan coil units maintaining the indoor temperature may lead to an insufficient supply of outdoor air for occupants and a substantial risk of overheating. Overall, the results of the analysis demonstrate that understanding risks is in some cases crucial to make an informed design decision regarding various energy saving design strategies.NSF ; Georgia Institute of Technology ; European Commission ; CEE