Medical Office Building Research Articles

Encourage volunteerism for team building

You know those really old people that volunteer at the hospital? Well, that now describes my husband and me. My husband drives a golf cart in the parking lots, carrying the visitors and patients to and fro. I sit at the front desk of one of the two medical office buildings that sit on the hospital campus. I smile, say hi, and answer simple questions. I’m not unlike the greeters at the big‐box stores, except I wear a red vest rather than a blue one.

Evaluating the applicability of a machine learning methodology to improve TMY weather file generation for different Canadian climate zones

Typical meteorological year (TMY) weather files are used in building energy simulations to represent typical weather conditions for a location. The conventional approach to generating TMY weather files uses a set of universal weighting factors determined based on expert judgment. These universal weighting factors can overlook the distinct weather patterns between different locations and their influence on energy performance. A previous study used machine learning to generate location-specific weighting factors with respect to building energy performance. The objectives of this paper are: (1) To assess the applicability of the previous study across varying Canadian climates; (2) To investigate the feasibility of using standardized climate zone-based weighting factors to reduce the computational time associated with extracting location-based weighting factors while still considering local climate conditions to facilitate wider adoption of the proposed methodology. The investigation is conducted for a medium office building for 18 locations across six Canadian climate zones and generates two weather files, TMYSTATION and TMYCZ, for each location. The TMYSTATION weather files are generated using location-based weighting factors for each location whereas the TMYCZ weather files are generated using climate zone-based weighting factors for each location. The coefficient of variation of the root mean square error (CVRMSE) and normalized mean bias error (NMBE) are used to compare the performance of the proposed weather files with conventional weather files using the energy demands obtained through building simulation. The TMYSTATION and TMYCZ weather files outperform the conventional weather files in predicting the long-term energy performance of buildings. Although the TMYSTATION files marginally outperform the TMYCZ weather files in representing the long-term weather data, the convenience of standardized climate zone-based weighting factors allows the approach to be widely deployed.

Sustainability of telework: Systematic quantification of the impact of teleworking on the energy use and emissions of offices and homes

Previous research has explored the impact of telework on homes and offices separately, but it is necessary to examine these domains together, as energy savings in one may be offset by increased consumption in the other. Therefore, the present study aims to fill this gap by quantifying the impact of telework on the energy use of homes and offices simultaneously. Using a medium office building reference model and four home models, the present study simulates telework scenarios from 0 % teleworking to 100 % teleworking in 20 % increments in six different Canadian climate zones in EnergyPlus. The results show homes and offices with technologies that adapt to occupancy levels (adaptable) consume less energy and produce less emissions compared to inadaptable ones. However, energy use associated with homes increases slightly due to longer hours of occupancy. Emissions associated with telework depend on the impact of telework on internal heat gains, climate zones, and sources of energy (emission factors). The results demonstrate that the increase in energy consumption associated with various teleworking scenarios ranges from approximately 0.6 %–6.1 %. Similarly, the increase in emissions varies, ranging from nearly 0.5 % to 7.6 %. The present study is the first comprehensive study that considers the home type and size and other statistical data for different Canadian climate zones. The results have major implications for employers and policymakers aiming to adopt telework as a sustainable practice. The results of this study create the foundation for future comprehensive studies on teleworker behavior, transportation, and the internet use associated with telework.

Optimizing energy efficiency and thermal comfort of green envelope applications in hot arid climate

Climate change and unresolved environmental challenges in arid environments negatively affect urban development. Previous literature tackled the significance of ecological approaches and building envelope optimization as main pillars in reducing energy consumption and enhancing energy efficiency and thermal comfort in buildings. This study aims to tackle an environmental simulation of implementing green roofs and green walls as an ecological strategy applied to the building envelope with considerations of the window-to-wall ratio (WWR) in contribution to enhancing the built environment’s energy efficiency and thermal comfort. The main study aimed to define the optimum solutions for applying ecological approaches on a medium office building envelope to investigate the enhancement of thermal comfort and total site energy. Hot arid climatic data was selected for its recent environmental challenges, and building envelope design, relying on experimental simulation research, a model was simulated using Design-builder software using discomfort hours and total site energy as the main objectives. Heating and cooling were added as outputs in the optimization to monitor their effect on the indoors. The two main output parameters were the WWR and envelope construction. Then a percentage decrease in the running cost was addressed. The multi-objective optimization showed an effective positive impact of green roof application on the building in hot arid climate than that of the green wall, which highlights the significance of green wall implementation to environmental and economic sustainable developments in arid environments.

Current Concepts in the Business of Orthopaedics.

Practice management within orthopaedic surgery demands a multifaceted skillset including clinical expertise, technical proficiency, and business acumen, yet the latter is rarely taught during orthopaedic training. As the healthcare system evolves in the United States, surgeons continue to face challenges such as decreasing reimbursements, increased regulatory burdens, and potential for practice acquisition. To remain competitive and provide exceptional care for patients, orthopaedic surgeons must cultivate a business-minded approach. This article highlights the growing significance of the business of orthopaedics and offers guidance on ambulatory surgical center ownership models, effective management of ancillary services, the effect of private equity in orthopaedic practice, real estate investment opportunities in medical office buildings, and the importance of brand recognition. By understanding these concepts, orthopaedic surgeons can exercise greater control over their practice's finances while providing quality care for their patients.

The interactive indoor-outdoor building energy modeling for enhancing the predictions of urban microclimates and building energy demands

There is a lack of an urban building energy modeling framework that considers the influence of surrounding buildings and local urban climate on building thermal performance. This can lead to inaccurate results since the thermal performance of individual buildings is heavily influenced by their surrounding built and climatic environment. This study establishes an interactive indoor-outdoor building energy modeling method to enhance the predictions of urban microclimates and building energy demands by coupling an urban physics model with a physics-based building energy model. Validation of the interactive coupling scheme uses field measurement datasets. Parametric simulation and analysis are conducted to understand the influence of the roof-to-canyon width ratio, canyon orientation, and ground vegetation fraction on canyon temperature, building energy consumption, and energy demand. Furthermore, the impacts of building energy model complexity (e.g., detailed vs. simplified building models) and coupling approaches on canyon temperature and building energy profiles are demonstrated using two case study buildings. In comparison with the one-way coupling approach, cooling energy consumption predicted with the dynamic two-way coupling approach varies by 3.5 % and 0.5 % for the detailed medium office building model and high-rise building model, respectively, and peak cooling demand varies by 8.4 % and 7.0 % for the detailed medium office building model and high-rise building model, respectively. This study also suggests that adopting a complex two-way coupling approach with environmental data exchange at various elevations is necessary for modeling tall buildings at the urban scale.

What Caused the EHR to Crash? Lessons Learned

After a power disruption in a medical office building led to a catastrophic shutdown of the IT servers and ultimately to a loss of the use of EHR and administrative IT systems, a root cause analysis was applied to identify the security threats to the IT systems of a multispecialty group and ways to mitigate this threat in the future.

An evaluation of the demand response potential of integrated dynamic window and HVAC systems

Demand response (DR) increases the flexibility and reliability of the electricity grid as use of intermittent renewable energy sources increases. HVAC and envelope DR measures present the largest aggregate energy and peak demand savings potential of all commercial building end uses because their net demand savings occur during critical peak demand periods. Controllable envelope measures include switchable electrochromic windows, operable window attachments such as outdoor louvers, roller shades, and awnings, as well as other innovative facade technologies that can modulate both solar heat gain and daylight admission over a broad solar-optical range. This study evaluated the technical potential of DR-enabled dynamic windows to reduce critical peak demand for a prototypical medium office building situated in all 16 U.S. climates. Model predictive control (MPC) algorithms were designed to minimize electricity cost in daylit perimeter office zones through control of an electrochromic window with and without HVAC thermostat setpoint control. Conventional and time-of-use rates were used to shape the degree of DR. Median annual peak demand savings with window and thermostat control across all climate zones were 24.3 kW (4.4 W/m2) per building or 15.9 W/m2 for non-north perimeter zones. Resource adequacy at the whole building level was estimated to be 13.1 to 43.4 $/kW per year over the 30-year life of the installation. Co-benefits were increased energy efficiency, and reduced electricity cost and emissions. Visual and thermal comfort requirements were met at all times. Dynamic facades controlled by MPC have substantial technical potential for DR across all U.S. climates and warrant serious consideration for inclusion in DR portfolios.

Empowering Owner-Operators of Small and Medium Commercial Buildings to Identify Energy Retrofit Opportunities

Small and medium commercial buildings account for nearly half of the energy consumed by commercial buildings in the United States. While energy retrofits can significantly reduce building energy consumption, buildings’ owners often lack the capital and experience to perform detailed energy audits and retrofit assessments. The purpose of this paper is to introduce a low-investment, bottom-up and simplified methodology for identifying energy retrofit opportunities that benefit the owners of small and medium sized office buildings In particular, the paper addresses small and medium commercial buildings on a university campus as a proof-of-concept for other owner-operators that have small and medium commercial facilities in their portfolio. The methodology consists of an eight-step framework using publicly-available and simplified tools. While energy audits and retrofit opportunity assessments are not new, a low-cost methodology for owner-operators of small and medium commercial buildings to analyze energy consumption and identify retrofit opportunities represents a contribution to knowledge. A medium office building on a university campus in Arizona served as a case study to validate the methodology. The case study showed a maximum potential energy reduction of an estimated 50%, but the figure varies based on the types of retrofit (deep versus light), energy conservation measures selected and implemented, invested resources, and interactive effects between measures. This methodology is extensible to other owner-operators that have building utility data and would like to perform retrofit opportunity assessments themselves.

Stochastic scheduling for commercial building cooling systems: considering uncertainty in zone temperature prediction

This paper presents the first attempt to address the uncertainty in zone temperature prediction with stochastic optimization. The uncertain zone temperature is a process uncertainty and has not been considered in the existing stochastic optimization for building control. To fill this gap, we proposed a novel formulation of stochastic optimization to handle process uncertainty in building control. Specifically, we first examined the accuracy of a typical linear model for predicting zone temperature. We then formulated the scheduling of the building cooling system as a stochastic optimization problem over a 24-hour look-ahead period to minimize the electricity cost of the studied building cooling system. After that, we applied the proposed stochastic load scheduling (SLS) to a direct expansion (DX) cooling system that serves a medium office building. Through simulation with a detailed building energy simulation software, EnergyPlus, we evaluated the operational cost and the thermal comfort compared with a deterministic load scheduling. The operation cost of scheduling was found to vary with the level of zone temperature prediction uncertainty. The proposed SLS can mitigate the impacts of uncertain zone temperature predictions on both operational cost and thermal comfort. The evaluation results indicate that the proposed SLS works better when the uncertainty level is more significant.

Simulation-based assessment of ASHRAE Guideline 36, considering energy performance, indoor air quality, and control stability

This study assesses American Society of Heating, Refrigerating and Air-Conditioning Engineers Guideline 36 (G36) with a typical medium office building. Specifically, this study employed a Modelica model of a variable air volume (VAV) system that serves this building, which includes components for representing indoor virus transmission and filtration. It then implemented the G36 control sequences for both water-side and air-side equipment in Python. After that, this study conducted the assessment by co-simulating G36 and the Modelica model using the Building Operations Testing Framework. Unlike existing works, this work has three unique features: (1) It considers the interactions between control sequences for water-side and air-side equipment of the studied VAV system. (2) It assesses the performance of G36 from the perspective of IAQ. (3) It examines the short-term behaviors of the studied building under G36 to understand the control stability. This assessment confirms significant energy savings from G36, largely because of the interaction between supply air temperature and hot water controls. It also reveals a trade-off between the ability to slow the spread of virus and the energy performance via demand controlled ventilation. Lastly, it emphasizes the necessity of tuning local feedback control when implementing G36.

Comprehensive analysis of model parameter uncertainty influence on evaluation of HVAC operation to mitigate indoor virus: A case study for an office building in a cold and dry climate

Simulation-based studies of HVAC operation to mitigate indoor virus have been conducted to understand tradeoffs between indoor air quality (IAQ) and energy consumption. However, the influence of model parameter uncertainty in these studies has not been systematically quantified, which is critical when providing guidance to building operators. To address this gap, we identify 20 model parameters for a typical medium office building system in a cold and dry climate that can influence IAQ and energy consumption for indoor virus scenarios. Next, the distributions of the parameter values are estimated from literature and a set of simulation samples for three representative days is generated that simultaneously sample all of the parameters from their distributions. Two HVAC virus mitigation strategies are studied: increased filtration using MERV 13 filters and increased ventilation, via supply of 100% outdoor air into buildings. The model parameter uncertainty leads to significant variability in the results, particularly for the IAQ because of the highly uncertain virus generation rate. Use of 100% outdoor air can be beneficial for some uncertain scenarios on the hot day, but shows less IAQ improvement and/or significant energy increases on the other days. The virus removal efficiency and pressure drop of the HVAC filter, fan efficiency, and internal heat gain are the most important parameters to determining the tradeoffs of the two strategies. The results demonstrate how this model parameter uncertainty analysis methodology can provide practical guidance to building operators.

An experimental study on round-trip efficiency of a preheating control with a medium office building

The interactions between building energy efficiency and demand response (DR) with buildings may complicate their impacts on the electricity grid and buildings, yet those interactions are not well understood. This work fills this gap by presenting an experimental study that quantifies the effects of DR on building energy efficiency. Unlike existing studies, this work 1) investigates the uncertainty levels when assessing the effects of DR; 2) studies the impact of rooftop heat pumps with direct expansion refrigerant-to-air coils on the round-trip efficiency. Specifically, we considered a medium office building (∼1860 m2), which is served by rooftop units, located in eastern Washington State. We performed preheating control tests during typical heating days in the year 2022 and compared the building’s energy consumption during the testing days to that during normal operation days under similar weather conditions. To understand how well those normal operation days represent the baseline for the assessment, the relationship between the energy performance of this building and weather conditions was also studied. Experimental results reveal that the round-trip efficiency (i.e., the ratio of discharging energy output from the building to charging energy input into the building) was between 0.16 and 0.92. The results show that significant energy loss may occur during the preheating process. It also suggests a significant correlation between the energy efficiency of the studied building under the preheating control and the outdoor temperature; and a highly nonlinear relationship between the zone temperature changing rate and the weather condition.

Simultaneous design and control optimization of smart glazed windows

The paper examines the benefits of simultaneous optimization of various design and control parameters for smart glazing windows of office buildings. The design variables include the window U-value, solar heat gain coefficient (SHGC), visible transmittance (Tvis), and window-to-wall ratio (WWR). The tint-switching control strategies reviewed include outdoor air temperature (OAT), indoor air temperature (IAT), incident total solar radiation (ITSR), and incident beam solar radiation (IBSR). These variables are optimized independently and simultaneously to determine the best specifications to minimize operating costs while maintained desired thermal and visual comfort levels. Specifically, electrochromic (EC) smart glazed windows are optimally designed and controlled when installed for a prototypical medium office building in Denver, Colorado. The optimization analysis results are considered to determine the breakeven installation costs required for smart glazing systems to be cost competitive compared to their static glazing counterparts. The analysis found that the annual energy cost savings from optimally designed and controlled smart glazed windows ranged from 11% − 18%. Of the design parameters, the U-value proved to be the most impactful on energy and cost reductions, followed by SHGC and WWR. Indoor and outdoor air temperature-based controls are determined the most effective operation strategies. Simultaneously optimizing for the design and control parameters provided the highest annual savings.

Individualized empirical baselines for evaluating the energy performance of existing buildings

The evaluation of building energy performance requires a baseline for comparison. Common empirical baselines are usually used for existing buildings since they are fast and convenient. However, the same type of building at the same location will receive the same baseline despite their difference in usage. Individualized baselines by creating building energy models are possible solutions, but it is labor intensive and time-consuming. To fill the gap, this study is to develop individualized empirical baselines for existing buildings in a fast way. First, common empirical baselines are created based on survey data. Then, to get training samples, building energy models for large-scale existing buildings are created and simulated. Finally, based on simulation results, mathematical models to get individualized empirical baselines in a fast way are created. U.S. medium office buildings were used as an example to demonstrate the method. We developed 30 mathematical models for medium office buildings in two vintages (constructed before 1980 and after 1980) and 15 climate zones. The mean absolute percentage errors (MAPE) between the individualized empirical baselines and the modeled baselines for those 30 mathematical models are all lower than 5.5%. An engineer can obtain the individualized empirical baseline for an existing building in a few seconds by using the open-source tool we developed.

Adaptive façade for building energy efficiency improvement by arithmetical optimization algorithm

SummaryTo improve the energy efficiency in buildings, a computational optimization method is suggested in this article. The method is designed based on the structure of the adaptive façade. This type of façade system can adjust its visible and thermal transmissivity for actively changing weather conditions. The main concept of this system is the optimization process. This process integrates the DesignBuilder as the building energy simulation tool with an optimization method, called arithmetical optimization algorithm, through the MLE+ toolkit. It is notable that the proposed approach can be applied to different building types and is also not involved in any specific optimization tool. In this regard, two case studies, a typical single office room, and a medium office building are selected to show the capability of the presented approach to improve the energy effectiveness of the building. Based on the results, the energy consumption is decreased by 15.0%–29.1% for the first case study and 14.3%–22.4% for the second case compared to the static façades. The adaptive façades' potentiality is indicated by the important achievements in this study.

The economic impacts of carbon emission trading scheme on building retrofits: A case study with U.S. medium office buildings

As a popular emission reduction tool, the carbon emission trading scheme (ETS) can potentially add an economic incentive for building owners to retrofit buildings in addition to the cost savings in energy. However, the additional economic benefits of building retrofits brought by ETS has not been quantitively investigated yet. To fill this gap, this study proposed a systematic economic evaluation method to investigate the economic impacts of ETS on building retrofits. The reduction of the payback period and the increase of the return on investment are adopted as evaluation metrics. Using medium office buildings as an example, this study predicted the economic impacts of ETS on building retrofits at four locations in the U.S., and three different carbon prices were investigated. The results show that carbon prices have significant economic impacts on building retrofits. With the relatively low forecasted time-variant carbon prices (around 10 USD per ton), the economic impacts of ETS on building retrofits are small. When carbon prices increase, the impacts of ETS would be up to 25% for 50 USD per ton (current prices in European Union) and 51% for 100 USD per ton. Furthermore, locations with more fossil energy have higher relative changes in the payback period and ROI but are more sensitive to carbon prices.

Tradeoffs among indoor air quality, financial costs, and CO2 emissions for HVAC operation strategies to mitigate indoor virus in U.S. office buildings

Adapting building operation during the COVID-19 pandemic to improve indoor air quality (IAQ) while ensuring sustainable solutions in terms of costs and CO2 emissions is challenging and limited in literature. Our previous study investigated different HVAC operation strategies, including increased filtration using MERV 10, MERV 13, or HEPA filters, as well as supplying 100% outdoor air into buildings for a system initially sized for MERV 10 filtration. This paper significantly extends that research by systematically analyzing the potential financial and environmental impact for different locations in the U.S. The previous medium office building system model is improved to account for operation in different climates. New evaluation metrics are created to consider the comprehensive impact of improving IAQ on costs and CO2 emissions, using dynamic emission factors for electricity generation depending on the location. HVAC operation strategies are studied in five different locations across the United States, with distinct climates and electricity sources. In four of the five locations, MERV 13 filtration offers the best improvement in IAQ per increase in costs and emissions relative to MERV 10. The exception is the mildest climate of San Diego, where use of 100% outdoor air provides the best IAQ with a limited increase in costs and emissions. A system not sized for HEPA filtration can lead to increased costs and emissions without much improvement in IAQ.

In-duct phase change material-based energy storage to enhance building demand flexibility

This paper presents a novel energy storage solution by incorporating phase change material (PCM) panels in supply ducts to increase a building’s thermal storage capacity and demand flexibility. During off-peak hours, the system runs at a supply air temperature (SAT) below the PCM solidification point to charge the storage unit with “cooling” energy. During on-peak hours, a higher SAT is utilized so that the stored “cooling” energy can be discharged into the supply-air as a means to reduce the peak air-conditioning power usage. To evaluate the potentials of peak demand reduction and utility cost savings, a numerical model for a PCM panel prototype and its heat exchange with the air flow in the duct was developed and calibrated using experimental data. Whole building energy simulations were conducted in a co-simulation environment that has integrated the developed PCM model, EnergyPlus Department of Energy (DOE) prototypical model for a medium office building and a calibrated model for variable-speed direct-expansion cooling systems. The simulations covered five cities in different U.S. climate zones over a three-month cooling season and used actual time-of-use (TOU) rate schedules offered by the local electric utility companies. The simulation results have shown the PCM storage could reduce the on-peak energy consumption by 23–32% and the seasonal cooling electricity cost by up to 16%, with a simple rule-based control strategy. A simple payback analysis resulted in payback periods from 7.5 to 27 cooling months.

Long-term carbon emission reduction potential of building retrofits with dynamically changing electricity emission factors

Buildings account for approximately 36% of the United States’ total carbon emissions and building retrofits have great potential to reduce carbon emissions. Current research adopts a constant electricity emission factor although it changes over time due to the increase of renewable energy generation. To accurately predict emission reduction potential of building retrofits, this study develops a novel method by using dynamically changing electricity emission factors. Using medium office buildings as an example, we predicted emission reduction of eight building retrofit measures from 2020 to 2050 in five locations in the U.S. with distinct climates and renewable adoption rates. To evaluate emission reduction potential sensitivity to the compositions of electricity generation, five scenarios for renewable energy adoptions are investigated. The results reveal several new phenomena on emission reduction potential of building retrofits for medium offices in the U.S.: (1) it decreases from 2026 to 2050; (2) it has the same trend with coal usage; and (3) it reaches the maximum under the high renewable cost scenario. Based on the results, it is recommended that building retrofits should focus on 1) improving lighting and equipment efficiency; 2) locations with higher coal usage rate, and 3) buildings under the high renewable cost scenario. The new method can also be used for predicting emission reduction potential of the building sector in the U.S. by applying to other building types and regions.