Energy usage modeling for heating and cooling of off-grid shelters
Introduction
Most humanitarian missions, including disaster relief and refugee camps, as well as military missions, are off-grid and require the use of liquid fuels for the local generation of electricity. For example, military forward operating bases (FOB) are typically located in remote areas, often in regions of conflict. Increased demand for fuel generates challenges and risks to the military forces in operation. Transporting fuel to the FOBs is a time-consuming and cost-intensive task, and with more time spent in transporting fuels, more personnel are exposed to risks. Lowering the use of petroleum fuels would increase financial benefits and would also decrease the risks to the soldiers, increasing combat effectiveness and mobility [1]. In the military FOBs, a large portion of the operational energy demand comes from heating, ventilation, and air conditioning (HVAC) needs of the temporary structures, known as shelters. The largest non-propulsion consumers of liquid fuels are HVAC systems, which consume as much as 60% of the fuel allocated for an FOB during extreme weather periods [2,3]. The energy consumption of these shelters plays a crucial role in the overall energy demand of these off-grid camps. The need for energy to support HVAC systems in temporary structures is found not only at military bases, but also at humanitarian camps in various emergency situations, such as natural disasters. The most widely used emergency shelters are deployable tents, which have the benefits of ease of transportation and installation. However, indoor living conditions may be affected by exposure to extreme weather in some climate zones. The addition of HVAC systems to the shelters is frequently necessary to avoid further health-related problems to occupants [[4], [5], [6]]. The availability of reliable electrical power is not guaranteed in such emergencies. Therefore, effective management of fuel usage is crucial, and to decrease the frequency of fuel delivery it is important to predict the minimum amount of fuel needed for a given mission.
Much work has been done on the energy analysis of commercial buildings, using energy simulation tools to investigate possible energy savings. Study of the building energy models and validating them to analyze the actual building energy usage has been a topic of interest for several decades [7,8]. The accuracy of the model has since been continuously improved due to the development of the modeling methods as well as improved computational resources [9]. More recently, state-of-the-art building energy analysis includes the introduction of new and unconventional materials or systems into the model to seek energy performance advantages to the buildings [[10], [11], [12], [13]]. Most of these earlier studies and various recent studies are mainly focused on developing modeling and validation of the energy models for traditional buildings including typical residential buildings and commercial buildings [[14], [15], [16], [17]].
While topics for traditional building energy models are well established, there has also been increasing efforts to research the area of temporary or emergency shelters, as needs for these shelters rose rapidly in recent years due to continued disasters around the world [6]. The studies included a wide variety of topics such as the design of the new system for expandable structures [18], structural evaluation of emergency shelters [19], and methods of building shelters using recycled materials [20,21]. Obviously, evaluating the energy and thermal performance of these shelters has also been one of the main interests. The military used and civil used shelters have been constantly tested for their performance of energy efficiency and indoor comfort under extreme weather conditions. For example, Flanders tested the performances of an air-transportable shelter during cold environments in Alaska and improved the thermal comfort as well as ease of deployment [22], and Pilsworth proposed a simple method of calculating heat losses from tents based on wall conductions and air infiltrations [23]. However, these earlier studies are mostly based on case studies of field tests, and did not fully consider important factors for lightweight shelters (compared to buildings) such as weather variations, occupancy, or ground effects.
As it became a common practice to use software programs for modeling building energy, energy models for temporary shelters were also used to support the studies on the thermal properties of these shelters. Kim et al. used energy model simulations (EnergyPlus) for a hard-walled temporary housing unit to predict indoor thermal comfort [24]. Crawford et al. modeled different prototype shelters and tested their performance under cold conditions using simulation models (ESP-r), which were validated using experimentally measured data from erected shelters [5]. Slavalai et al. tested the effectiveness of adding multilayer insulators to shelters by generating an energy model for emergency shelter using an in-lab measurement of material properties [6]. Computational fluid dynamics (CFD) modeling has been also used to analyze shelter performance under different conditions [25,26].
However, compared to thermal energy modeling for commercial and residential buildings, which can be easily done with readily available energy modeling software, there have been relatively few studies based on the energy modeling of shelters. Only a few types of shelters have been modeled by energy simulation tools, and the methods for generating and validating these models vary greatly, which has resulted in inconsistent simulation results. Furthermore, the majority of these studies were mainly focused on the shelter's performance in cold weathers only [5,6,22,23,26]. Thus, a significant opportunity exists for energy optimization and fuel consumption reduction for temporary shelters through reliable shelter energy models. Therefore, this work aims to develop a general approach that incorporates experimental validation.
The goal of this study is to develop a generalized shelter energy modeling methodology, including the experimental validation of the model. This is achieved by generating an OpenStudio energy model of a sample soft-wall shelter with procedures to acquire reliable inputs, and validating the model performance with field measured data. Parametric simulations are subsequently performed to investigate the effectiveness of new materials in reducing heat loss and the resulting energy savings.
Section snippets
Methods
Modeling expeditionary shelters, especially soft-walled tents, is challenging since many environmental factors must be taken into account. While conventional buildings depend more on wall conduction heat transfer, shelters, with their thinner surfaces, are significantly affected by convection and radiation heat transfer. Therefore, any model for such shelters must include precise convection and radiation properties. Furthermore, with their direct thermal connection to the ground, the thermal
Modeling procedure
Each shelter model in the present study is a replication of a military structure (shelter) used in forward operating bases (FOB). The model has identical properties to an actual shelter, including geometry/dimensions, materials, construction, internal loads, and infiltration. These models are generated in an OpenStudio model (OSM) format, which can be read by the OpenStudio software.
Field measurements
An HDT Base-X 305 shelter, was deployed in a test field located in Strafford, NH with the purpose of gathering data under actual operating conditions, which is used to compare with OpenStudio model simulation results and to validate the fidelity of the developed shelter model. The Base-X 305 shelter was chosen for this study since it is widely used in deployed FOBs [34].
In addition, the floor area of 18′ x 25’ is a size of standard military shelters produced by various vendors, thus the results
Validation
Validation was performed by comparing results from the OpenStudio model and measured data [34] during the two different measurement condition periods.
Application of advanced materials
Further study was performed to identify possible improvements by using advanced materials, two advanced materials are introduced to the shelter construction: aerogel insulation and radiant barrier. The materials are put in as additional layers of material at the outer surface of the interior liner (facing the gap zone), following how additional materials such as insulations are added in the actual shelter configurations. OpenStudio simulations are performed throughout the similar period as in
Conclusions
An OpenStudio model of HDT Base-X305 soft shell shelter was generated with an air-conditioning (A/C) unit, and the climate characteristics and A/C demand were compared with field data. The indoor temperature agreed with an average error of ~3 °C during the unconditioned period, and the HVAC load showed an average error of 0.64 kWh during the conditioned period. Sensitivity analysis showed that the effect of the infiltration value and insulation R values are significant, suggesting that the
Author statement
The work described here has not been published previously (except in the form of an academic thesis). It is not under consideration for publication elsewhere, its publication is approved by all authors and tacitly or explicitly by the responsible authorities where the work was carried out. If accepted, it will not be published elsewhere in the same form, in English or in any other language, including electronically without the written consent of the copyright-holder.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
The authors acknowledge support for this work from the Office of Naval Research award N000141420001, under the Energy Efficient Outpost Modeling Consortium (EEOMC), with Dr. Mark Spector as Program Manager.
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