Comfort Satisfaction Research Articles

The impact of LEED certification on energy performance and occupant satisfaction: A case study of residential college buildings

This article investigates the energy consumption and occupant comfort of a LEED-certified residential college building compared to non-LEED-certified buildings on a university campus. Eight residential buildings, including one LEED-certified building (ranked silver) and seven non-LEED-certified buildings, were selected as a case study. Several data collection methods have been used to gather data regarding building physical features, weather data, monthly electricity, natural gas and water consumption, occupancy information, and occupant level of comfort and satisfaction. In addition, several data analysis methods have been used in this study to investigate the impact of LEED certification on energy consumption and occupant comfort in the studied residential college buildings. This study also investigates occupants’ levels of satisfaction in different areas, including room temperature, water temperature, water pressure, air quality, natural and artificial lighting amount, and overall comfort, by conducting a survey. The results showed that the studied LEED-certified building had higher energy consumption rates but also a higher satisfaction rating for overall comfort compared to the non-LEED-certified buildings. It is concluded that the higher energy consumption of the LEED-certified building is because of its low score in the category of energy and atmosphere, while its better performance in overall comfort satisfaction is because of its acceptable score in the category of indoor environmental quality on its LEED scorecard.

Predictive and probabilistic modelling using machine learning for building indoor climate control

For the last few decades, thermal comfort has been considered an aspect of sustainable building evaluation methods and tools. However, estimating the indoor air temperature of buildings is a complicated task due to the nonlinear behaviour of heating, ventilation and air conditioning systems combined with complex dynamics characterized by the time-varying environment with disturbances. This issue can be alleviated by modelling the building dynamics using Gaussian processes since it also measures the uncertainty bounds. The main focus of this paper is designing a predictive and probabilistic room temperature model of buildings using Gaussian processes and incorporating it into model predictive control to minimize energy consumption and provide thermal comfort satisfaction. We exploited the Gaussian processes’ full probabilistic capabilities as the mean prediction for the room temperature model and used the model uncertainty in the objective function not to lose the desired performance and to design a robust control scheme. We illustrated the potentials of the proposed method in a numerical example with simulation results.

Breathable and Wearable Strain Sensors Based on Synergistic Conductive Carbon Nanotubes/Cotton Fabrics for Multi-directional Motion Detection.

Flexible strain-sensitive sensors have been receiving intensive attention in many aspects ranging from human motion capture to health-related signal monitoring. However, the fabric strain sensor with multi-directional sensing capability, besides having a wide strain range and high response sensitivity, is still very challenging and deserves further exploration. Here, we have prepared a wearable cotton fabric strain sensor uniformly decorated with single-walled carbon nanotubes through a facile solution process. The unique hierarchical architecture of the cotton fabric woven from twisted yarns combined with the conductive carbon nanotube network endows the fabric strain sensors with attractive performance, including low detection limit, large workable strain range, fascinating stability and durability, excellent direction-dependent strain response, and good air permeability. The strain sensor without polymer encapsulation can not only monitor subtle and large multi-directional motions but also fit well to the human body with satisfactory comfort, demonstrating its potential application in wearable electronics and intelligent clothing.

Effects and Satisfaction of Comfort Nursing plus Psychological Nursing in the Clinical Nursing of Neurology Patients: A Comparative Study.

Objective To explore the effects and satisfaction of comfort nursing plus psychological nursing in the clinical nursing of neurology patients. Methods In this prospective study, 90 neurology patients admitted to our hospital from January 2019 to January 2020 were recruited and randomized into a control group and an experimental group with 45 cases in each group. The control group received routine care, and the experimental group received comfort care plus psychological care. The comfort scores and nursing satisfaction of the two groups were compared. The Hospital Anxiety and Depression Scale (HAD) was used to assess the emotional state of patients before and after the intervention. The Exercise of Self-care Agency Scale (ESCA) was used to assess the patient's self-care ability after the intervention. Results The comfort scores of the experimental group were higher than those of the control group (P < 0.05). The experimental group showed significantly higher satisfaction than the control group (P < 0.05). Patients in the experimental group had lower HAD scores after intervention than those in the control group (P < 0.05). After the intervention, the experimental group had higher ESCA scores and a higher Barthel index than the control group (P < 0.05). Conclusion Comfort nursing plus psychological care improves nursing satisfaction and self-care ability of neurology patients and relieves their negative emotions.

Chest CT tomography vs. intracavitary electrocardiogram guidance in predicting the length of PICC placement

BackgroundTo evaluate chest computed tomography (CT) compared to intracavitary electrocardiogram (ECG) in predicting the length of peripherally inserted central catheter (PICC) placement and analyzing the accuracy of the positioning methods.MethodsThis study included a total number of 436 patients who underwent PICC placement. The patients enrolled were randomly divided into two groups: ECG group (n = 218, received IC-ECG) and chest CT group (n = 218, received chest CT). The tip length of the catheter in the superior vena cava, the measured length of the catheter and the actual insertion length of the catheter were observed and recorded in the two groups.ResultsThe best catheterization rate of tip positioning and the one-time placement rate of tip positioning in ECG group were significantly higher than that in the chest CT group (all P < 0.05). The comfort level and satisfaction rate in ECG group was significantly higher than that of chest CT group (all P < 0.05).ConclusionAccurate catheterization length could be achieved by both chest CT and intracavitary electrocardiogram guidance in the process of predicting PICC placement length. However, IC-ECG guided procedure was more worthy of promotion in clinic.

Activity, socket fit, comfort and community participation in lower limb prosthesis users: a Cambodian cohort study

BackgroundAfter amputation, many people become less active, feel lonely and lose independence. Understanding the factors associated with low physical activity levels and participation could contribute to defining key interventions which can support prosthesis users so they can live a more active and socially included lifestyle. This longitudinal observational study aims to assess relationships between physical activity, community participation, prosthetic fit, comfort and user satisfaction using actimetry, 3D scans and questionnaires in a Cambodian cohort of established lower limb prosthesis users.MethodsTwenty participants (5F:15M, nine transfemoral, eleven transtibial, 24–60 years old and 3–43 years since amputation) were recruited. They completed a questionnaire which included their demographics, community participation, prosthesis satisfaction and comfort at the start of the study, and between three and six months later. Their prosthetic sockets and residual limbs were 3D scanned at the start and end of the study. Accelerometers were embedded under the cosmesis on the shank of the prosthesis, to collect ten weeks of activity data.ResultsParticipants averaged 4470 steps/day (743–7315 steps/day), and wore their prosthesis for most waking hours, averaging 13.4 h/day (4.5–17.6 h/day). Self-reported measures of activity and hours of wear correlated with these accelerometer data (Spearman’s rho rs = 0.59, and rs = 0.71, respectively). Participants who were more active wore their prosthesis for more hours/day (Pearson r = 0.73) and were more satisfied with socket fit (rs = 0.49). A longer residual limb correlated with better community participation (rs = 0.56) and comfort (rs = 0.56). Self-reported community participation did not correlate with a person’s activity level (rs = 0.13), or their prosthesis comfort (rs = 0.19), and there was only weak correlation between how important the activity was to an individual, and how often they participated in it (rs = 0.37). A simple 0–10 scale of overall comfort did not provide enough detail to understand the types and severity of discomfort experienced.ConclusionAssociations between perceived and measured activity levels correlated with socket satisfaction in this cohort of people with established lower limb amputations. The small sample size means these correlations should be interpreted with caution, but they indicate variables worthy of further study to understand barriers to community engagement and physical activity for prosthesis users in Cambodia, and potentially in other settings.

Construction of 3D Design Model of Urban Public Space Based on ArcGIS Water System Terrain Visualization Data

On the premise of being familiar with ArcGIS Server technology, we build the architecture of the entire platform, including the basic support layer, data layer, service platform layer, and application layer, and build the entire environment of the platform. We make electronic maps through Arc Map, and collect, organize, and improve spatial data and attribute data, so as to achieve satisfactory accuracy and visual comfort. This study implements various map services under the Dojo framework, including basic map operations, information display and query, marker points, eagle eye diagrams, measurement, printing, and other functions, and uses JavaScript technology to improve user experience. We publish various services through ArcGIS Server, and realize fast and error-free invocation of each service. Based on the theory of runoff and runoff, ArcGIS software was used to study the hydrological information of the watershed, and to determine the catchment area threshold and hydrological response unit. Combined with the GIS spatial analysis method, the numerical simulation of rainfall and runoff in the study case area was carried out, and the variation of the annual rainfall-runoff coefficient was obtained. This study selects an area where stock planning was first proposed as the object of this research. Briefly, we introduce the construction of three-dimensional public space in a certain area, select thirteen typical three-dimensional public spaces as representatives for public evaluation, and explore their existing problems, mainly including the lack of adaptability of space functions and the lack of diversity in space design, privatization of operation management, low level of public perception, etc. Since then, in response to the public problems of the three-dimensional public space in a certain area, a targeted three-dimensional public space optimization strategy is proposed from the four levels of planning policy, urban design, management subject, and user subject.

Impact of Population Density on Physical Environmental Quality

This study aims to identify and assess population density that causes slums and physical effects on the environment in the Simpang Dago area. The methodology used is a qualitative research method on the object's condition by conducting a literature study and collecting related documents. The study was conducted with a case study in one area in the city of Bandung. The results showed that the achievement of comfort, safety, health, and mutual satisfaction is expected to help reduce population density impact in the Simpang Dago area. To achieve that goal, a study of population density impact on the quality of the physical environment. The solution of densely populated areas problem by relocating residents and providing affordable vertical housing by considering various aspects. The implication of this study's results is due to the dense population and houses' distance is too close; therefore residents around the Simpang Dago area must be concerned about their environment's cleanliness. In addition, not all population density gives negative impacts to the quality of an area's physical environment, depending on the residents' awareness.

Solar Energy Compensation for Building Energy Saving with Thermal Comfort in a Cold Climate

This paper proposes an energy-saving strategy with assistance from solar thermal compensation for building energy systems. The target of the control strategy was to minimize energy consumption under thermal comfort constraints in buildings. First, the factors influential to indoor temperature in building environments were analyzed. Secondly, the internal and external factors, such as building materials; building orientation; window size; heating, ventilation, and air conditioning (HVAC) facilities; blinding device; solar irradiation; wind speed; and outdoor temperature were used to construct a building model on the platform ENERGYPLUS (E+). A controller aiming to regulate the amount of solar irradiation was developed with the Building Controls Virtual Test Bed (BCVTB) tool. Afterward, the building performance under different strategies was tested by co-simulation using both the computational platforms, E+ and BCVTB. The optimum scheme achieved 30.6% energy savings while meeting the same comfort criterion of its competition strategy. The study verified that the proposed strategy of combined heating, ventilation, and air conditioning and blind control could realize the energy savings and comfort satisfaction at the same time. The proposed method provides a reference to the development of low-/zero-energy building concepts in the field.

Lessons learned from PCM embedded radiant chilled ceiling experiments in Melbourne

Buildings are responsible for over a third of energy consumption worldwide, particularly due to the increasing demand for air-conditioners in response to the more extreme heat around the globe. It is imperative to move towards more energy-efficient space cooling alternatives. The integration of phase change material (PCM) with radiant chilled ceilings (RCC) is a promising technology due to its benefits regarding energy efficiency and indoor environmental quality. This article presents a field study conducted on a newly-developed PCM embedded radiant chilled ceiling (PCM-RCC) installed in a stand-alone cabin located in Melbourne. The study evaluates the thermal and energy performance of the system through investigations of the transient thermal behaviour of PCM panels in charging-discharging cycles, the indoor comfort conditions, and the electricity peak demand. It was observed that the proposed PCM-RCC can provide satisfactory comfort conditions and contribute to load shifting if a refined operating strategy is applied. The efficiency of PCM recharge overnight depends on several factors that need to be carefully considered in design. The challenges related to the implementation of optimal operating dynamic schedules in response to the thermal behaviour of PCM-RCC, and accurate weather forecasting should be addressed to realise the full potential of this technology.

A novel thermal comfort and energy saving evaluation model for radiative cooling and heating textiles

Personal thermal management (PTM) techniques, which establish local thermal envelopes around the human body instead of cooling/heating the entire building space, have great potential for thermal comfort satisfaction and building energy saving. As a promising technique for PTM, novel radiative cooling/heating textiles have been investigated by many researchers. However, there lacks good evaluation method for such novel radiative cooling and heating textiles to verify their thermal performance. The objective of this work is to build a comprehensive thermal comfort and energy saving evaluation model for novel textiles. Firstly, a naked human body model is built and validated by experimental data. After that, the clothing model is added and the heat loss of the human body at different ambient temperatures is analyzed and compared with experimental results. All experimental data for validation are obtained from the literature. Then, the thermal comfort model and the energy saving model are used to obtain the effectiveness of novel textiles. In addition, the effect of air gap thickness on thermal comfort and energy saving is also thoroughly discussed. It is concluded that the thermal comfort HVAC temperature setpoint would increase 0.2 ∼ 2.8 °C (cooling) and decrease 0.8 ∼ 4.4 °C (heating) at air gap thickness δ = 5 mm (compared to HVAC cooling setpoint of 23.0 °C, and heating setpoint of 22.0 °C). More importantly, the use of novel radiative cooling/heating textile could reduce up to 39.4%/44.2% building energy consumption.

Design optimization of urban typologies: A framework for evaluating building energy performance and outdoor thermal comfort

• A computational workflow is implemented, and a multi-phase optimization framework is developed for evaluating building energy performance and outdoor thermal comfort. • The framework is tested for various low-rise, mid-rise, and high-rise theoretical urban typologies in Syracuse, New York. • Tradeoffs between energy performance and outdoor thermal comfort are studied by energy use and outdoor thermal comfort autonomy, respectively. In the physics-based simulation of urban geometries, the outdoor environment was usually simulated separately from buildings – until recently, when the holistic assessment of the urban environment began to attract more attention. Although analyzing design alternatives with multiple objectives is still a challenge, computational tools enable generating thousands of scenarios to rapidly assess performance corresponding to a specific goal. In this study, we developed a multi-phase optimization framework for conceptual urban design. We tested this framework for urban typologies in Syracuse. The energy performance of each alternative was compared with a baseline. The alternatives that generate wasteful energy performance were filtered out first, then remaining scenarios that performed better than the baseline were analyzed using outdoor thermal comfort autonomy (OTCA). Mid-rise multifamily buildings showed the best performance (55.8% energy improvement compared to the baseline). Although hot week outdoor comfort satisfaction among selected mid-rise typologies was high (92.9–98.5%), the satisfaction in cold week was very low (between 8.4–11.6%) among them. This framework contributes to identifying an acceptable range of design solutions by broadening the perspective of the field toward using a more customized optimization framework in early design that will further guarantee the requirements of energy efficient and sustainable cities.

Supervisory optimal control using machine learning for building thermal comfort

For the past few decades, control and building engineering communities have been focusing on thermal comfort as a key factor in designing sustainable building evaluation methods and tools. However, estimating the indoor air temperature of buildings is a complicated task due to the nonlinear and complex building dynamics characterised by the time-varying environment with disturbances. The primary focus of this paper is designing a predictive and probabilistic room temperature model of buildings using Gaussian processes (GPs) and incorporating it into model predictive control (MPC) to minimise energy consumption and provide thermal comfort satisfaction. The full probabilistic capabilities of GPs are exploited from two perspectives: the mean prediction is used for the room temperature model, while the uncertainty is involved in the MPC objective not to lose the desired performance and design a robust controller. We illustrated the potential of the proposed method in a numerical example with simulation results.

Nonlinear Moving Horizon Estimation and Model Predictive Control for Buildings with Unknown HVAC Dynamics

We present a solution for modeling and online identification for heating, ventilation, and air conditioning (HVAC) control in buildings. Our approach comprises: (a) a resistance-capacitance (RC) model based on first order energy balance for deriving the zone temperature dynamics, and (b) a neural network for modeling HVAC dynamics. State estimation and model identification are simultaneously performed using nonlinear moving horizon estimation (MHE) with physical constraints for system states. We leverage the identified model in model predictive control (MPC) for occupant comfort satisfaction and HVAC energy savings and verify the approach using simulations. Our system relies only on building management system data, does not require extensive data storage, and does not require a detailed building model. This can significantly aid the large scale adoption of MPC for future occupant-centric control of grid-interactive buildings.

Denture Satisfaction – The Most Wanted Key to Successful Complete Denture Therapy.

Abstract:&#x0D; Background: The dilemma of patient satisfaction vs. non-satisfaction with dentures is another never-ending debate in dentistry. The fabrication of optimal dentures is possible with appropriate prosthetic laboratory techniques along with patients’ anatomic and physiologic requirements assessed by a dentist.&#x0D; Aim : The purpose of this study was to evaluate the patient’s priority and mean satisfaction scores of the patient and dentist during complete denture therapy.&#x0D; Material and methods: After selecting the subjects based on decided inclusion and exclusion criteria, the patients were asked to fill the proforma with VAS. The proforma contained a questionnaire. The patients rated their dentures using a scale ranging from 1-5.&#x0D; Results: According to the patient’s priority the majority of the patients preferred mastication. The highest mean dentist satisfaction score was concerned with the extension of a denture. There was no statistically significant difference with age and gender for mean denture assessment, aesthetic, phonetics, mastication and comfort satisfaction score. However, the employed patients have aesthetic, phonetics and mastication satisfaction score higher than unemployed patients and the relationship was statistically significant.&#x0D; Conclusion: Majority of the patients was concerned with better chewing function with their dentures. Age and gender do not affect patient satisfaction. However, employed patients were less satisfied with their dentures as compare to unemployed patients. In addition, patients who were educated had better phonetics with their dentures as compare to uneducated patients. Strong dentist-patient communication is necessary to be able to satisfy a patient.&#x0D; Keywords: Complete denture, Satisfaction, Patient communication&#x0D; &#x0D;

Analysis of Customer Satisfaction Level on International Departure Terminal Waiting Room Facilities at Sultan Syarif Kasim II International Airport

The waiting room facilities service is very important to increase comfort and increase customer satisfaction. Improving services in terms of waiting room facilities needs to be done from time to time because the dynamic nature of customers and because of any customer tendency that wants to get something more and different. The research objective that wants to be achieved in this study is to know how the international departure terminal waiting room facilities at Sultan Syarif Kasim II International Airport influence on the customer satisfaction level. In this study, the population of the research is the users of the Sultan Syarif Kasim II International Airport flight services, especially the international departure terminal. The obtained research result has shown that the formulated hypothesis in proven that the international departure terminal waiting room facilities at Sultan Syarif Kasim II International Airport have a positive and significant influence on the customer satisfaction level.

Data-driven control of room temperature and bidirectional EV charging using deep reinforcement learning: Simulations and experiments

The control of modern buildings is a complex multi-loop problem due to the integration of renewable energy generation, storage devices, and electric vehicles (EVs). Additionally, it is a complex multi-criteria problem due to the need to optimize overall energy use while satisfying users’ comfort. Both conventional rule-based (RB) controllers, which are difficult to apply in multi-loop settings, and advanced model-based controllers, which require an accurate building model, cannot fulfil the requirements of the building automation industry to solve this problem optimally at low development and commissioning costs. This work presents a fully data-driven pipeline to obtain an optimal control policy from historical building and weather data, thus avoiding the need for complex physics-based modelling. We demonstrate the potential of this method by jointly controlling a room temperature and an EV to minimize the cost of electricity while retaining the comfort of the occupants. We model the room temperature with a recurrent neural network and use it as a simulation environment to learn a deep reinforcement learning (DRL) control policy. It achieves on average 17% energy savings and 19% better comfort satisfaction than a standard RB room temperature controller. When a bidirectional EV is connected additionally and a two-tariff electricity pricing is applied, it successfully leverages the battery and decreases the overall cost of electricity. Finally, we deployed it on a real building, where it achieved up to 30% energy savings while maintaining similar comfort levels compared to a conventional RB room temperature controller.

A survey-based approach used to analyse the indoor satisfaction and productivity level of user in smart working during lock-down due to the COVID-19 pandemic

Italy was the first country in Europe to enter lock-down due to COVID-19 pandemic. Most employees have been forced to adopt a work at home solution to avoid any possibility of spreading the virus. The article presents the results of a survey carried out in March-June 2020, during the first lockdown in Italy, aimed at investigating how people perceive the Indoor Environmental Quality (IEQ) of their households during working from home. The questionnaire consists in a general section reporting information about participant, households and rooms where they perform the working activities; a specific section reporting feedbacks on each IEQ aspects (thermal, visual comfort, air and acoustic quality), overall comfort, productivity and other external variables that can affect users’ well-being during working hours. A total of 330 participants from all over the Italian territory signed the consent to participate in the survey over a period of about 3 months. The dataset was used to define the global level of satisfaction, perception, preference and interference with work at home, considering the main indoor environmental factors. The Machine Learning (ML) approach was applied to identify the most useful model to predict the overall comfort satisfaction.

Deep Reinforcement Learning for room temperature control: a black-box pipeline from data to policies

Deep Reinforcement Learning (DRL) recently emerged as a possibility to control complex systems without the need to model them. However, since weeks long experiments are needed to assess the performance of a building controller, people still have to rely on accurate simulation environments to train and tune DRL agents in tractable amounts of time before deploying them, shifting the burden back to the original issue of designing complex models. In this work, we show that it is possible to learn control policies on simple black-box linear room temperature models, thereby alleviating the heavy engineering usually required to build accurate surrogates. We develop a black-box pipeline, where historical data is taken as input to produce room temperature control policies. The trained DRL agents are capable of beating industrial rule-based controllers both in terms of energy consumption and comfort satisfaction, using novel penalties to introduce expert knowledge, i.e. to incentivize agents to follow expected behaviors, in the reward function. Moreover, one of the best agents was deployed on a real building for one week and was able to save energy while maintaining adequate comfort levels, indicating that low-complexity models might be enough to learn control policies that perform well on real buildings.

Study on the performance of interactive cascade ventilation oriented to the non-uniform indoor environment requirement

With the targets to achieve carbon neutrality and carbon emissions peak, numerous energy-saving and emission-reduction measures have been studied. In this study, a novel ventilation system named Interactive Cascade Ventilation (ICV) was proposed to save building energy consumption along with indoor thermal comfort satisfaction. A comparative experiment was conducted to compare this novel ICV with traditional stratum ventilation (SV) and mixed ventilation (MV). Draught rate (DR), temperature drop per unit cooling capacity (TDCC) combined with local coefficient of cooling capacity utilization (LCU) were introduced as the indices to comprehensively evaluate the thermal comfort and energy utilization. The results show that ICV, could enhance the local thermal comfort by 72.5% as compared to SV; improve TDCC by 23% and 30% as compared to SV and MV respectively; the lowest LCU of ICV confirmed that ICV has the strongest ability to control the local environment and delivers the most relative cooling capacity in the occupied area. The findings of this study confirm that ICV performs excellent in both indoor comfort and energy saving.