Search

Fe3O4 materials have many crystal forms, and the morphology of their nanomaterials is more diverse. Under the influence of nano-effects, they exhibit unique physical and chemical properties. The synthesized Fe3O4 materials with different morphologies have different properties. They are widely used in related fields such as electromagnetics, chemical engineering, catalysis, sensors, acoustics, medicine, environmental protection and so on. Choosing the appropriate contrast agent to display the anatomical characteristics of diseased and normal tissue is an important thing before using MRI (Magnetic Resonance Imaging) technology. At present, Gd-DTPA is a commonly used magnetic contrast agent in clinical practice, but Gd-DTPA has obvious shortcomings, such as short circulation time, non-specific distribution, and high price. In comparison, the superparamagnetic iron oxide nanocrystals have a high specific distribution in living tissues, mainly concentrated in reticular endothelial cells-rich tissues and organs, such as liver, spleen, lymph nodes and bone marrow. This study analyzed the imaging characteristics of 21 patients with unilateral benign sphenoid sinus disease who were confirmed by nasal endoscopic surgery and postoperative pathology. Among the 21 patients with unilateral benign sphenoid sinus lesions, 7 cases of them had cysts. Those with altered sphenoid sinus cavity expansion may be accompanied by thinning of bone resorption. MRI manifested as long T1 and long T2 irregular spherical signal shadows. 8 cases of them are fungal lesions. MRI showed mixed signals are in the sphenoid sinus, the flaky exudation showed a high signal, and the fungal nodule showed a low T2WI signal. In the 3 cases of cerebrospinal fluid rhinorrhea, MRI showed a line between the high-signal shadow of the cerebrospinal fluid and the high-signal liquid shadow in the sinuses. High signal and shadow are connected, and other tissues (brain tissue, nasal mucosa) show low signal. Fe3O4-based MRI technology can improve imaging quality and diagnostic efficiency.

Building energy systems, i.e. heating, ventilation, and air-conditioning (HVAC) systems, are essential for modern buildings. They provide a comfortable and healthy indoor environment. Design quality has significant impact on HVAC system efficiency. The typical building energy system design process involving several procedures is repetitive and time-consuming. It is often limited by the engineer's experience, capabilities, and time constraints; thus, the design in most cases barely satisfies building codes. In recent decades, computational intelligence (CI) has achieved substantial improvements in various fields. This paper presents a comprehensive review of using CI for HVAC system optimization design. Firstly, this paper analyzes seven procedures which constitute a typical HAVC system design process and finds that optimization problems encountered during design process can be divided into three categories: model estimation, decision making and uncertainty analysis. Then a brief introduction of CI techniques used to solve HVAC design optimization problems and detailed literature review of application examples are given. Though the design problem varies with each other, this paper outlines a typical workflow which is able to solve most HVAC optimization design problems. At last, a framework of an integrated HVAC automation and optimization design tool is proposed. The framework is developed based on building information modeling (BIM) and extracted typical design optimization workflow. It is able to connect various design stages by implementing structured information transfer between them and ultimately improve design efficiency and quality.

The energy performance and energy flexibility potential of a sorption-assisted water storage (SAWS) for a medium-scale residential building with eight apartments under the climatic condition of Potsdam, Germany were investigated. The SAWS system consists of a stratified water storage coupled to an adsorption heat pump (AHP). The driving heat source for the AHP was modeled as an ideal heater, which can be interpreted as an electric heater to serve as an off-peak storage heating system. Five representative partial heating loads of a building were investigated. Recharging situations of 2 h, 4 h, and 8 h with an interval of 2 h heater switching off were considered. Transient simulation results show that the 2 h heater switch off is feasible and does not significantly reduce the occupants’ thermal comfort in the four low heating load cases. However, for the highest heating load case, the load cannot be completely met. An average heating coefficient of performance of 1.33 for all the five load cases is achieved. Additionally, under the simple control scheme considered here, this SAWS system achieves high electricity flexibility by controlling the heater switch on and off schedule for a demand response program.

Fe₃O₄ materials have many crystal forms, and the morphology of their nanomaterials is more diverse. Under the influence of nano-effects, they exhibit unique physical and chemical properties. The synthesized Fe₃O₄ materials with different morphologies have different properties. They are widely used in related fields such as electromagnetics, chemical engineering, catalysis, sensors, acoustics, medicine, environmental protection and so on. Choosing the appropriate contrast agent to display the anatomical characteristics of diseased and normal tissue is an important thing before using MRI (Magnetic Resonance Imaging) technology. At present, Gd-DTPA is a commonly used magnetic contrast agent in clinical practice, but Gd-DTPA has obvious shortcomings, such as short circulation time, non-specific distribution, and high price. In comparison, the superparamagnetic iron oxide nanocrystals have a high specific distribution in living tissues, mainly concentrated in reticular endothelial cells-rich tissues and organs, such as liver, spleen, lymph nodes and bone marrow. This study analyzed the imaging characteristics of 21 patients with unilateral benign sphenoid sinus disease who were confirmed by nasal endoscopic surgery and postoperative pathology. Among the 21 patients with unilateral benign sphenoid sinus lesions, 7 cases of them had cysts. Those with altered sphenoid sinus cavity expansion may be accompanied by thinning of bone resorption. MRI manifested as long

As a means to adjust the temperature of the thermal zones in buildings, building thermal mass is regarded as one of the essential sources of energy flexibility. It is still challenging to quantify the energy flexibility of passive thermal mass, making it oppugning to use thermal mass for buildings’ demand response (DR). A method to accurately quantify the energy flexibility from heating, ventilation, and air conditioning systems (HVAC) is important for buildings to participate in DR projects. This paper proposes a novel data-driven model to quantify HVAC’s electrical demand under dynamic global temperature adjustment. The Markov chain is first used to implement an effective sampling method to produce a global temperature resetting schedule representing different temperature resetting. Next, EnergyPlus evaluates the HVAC electrical demand under the various temperature reset scenarios. In the end, the LightGBM algorithm is used to develop the data-driven model. Having validated the proposed model, the case study was conducted in a DOE reference office building for EnergyPlus. Results demonstrate that the Markov chain outperforms the probabilistic method when sampling temperature setpoint schedules. In the future, the proposed data-driven model can be used to evaluate the flexibility capacity of an energy management system in grid-integrated buildings.

In recent years, with the rapid growth of electricity demand and the development of smart grids, demand-side management had an important role. As the penetration rate of distributed renewable energy generation in the grid increases, the diurnal peak of the net load demand curve in the urban area is offset by renewable energy sources such as photovoltaics and the peak load time gradually shifts from afternoon to evening. The peak electricity load of residential buildings usually occurs in the evening, which aggravates the power balance problem. To this end, this study proposes a demand response (DR) scheduling approach for residential buildings, aimed for four types of residential building loads: interruptible and deferrable loads, noninterruptible and deferrable loads, noninterruptible and nondeferrable loads, and air conditioning loads. Nondominated sorting genetic algorithm II is used as a multi-objective optimization algorithm to search for the minimal electricity cost and minimal inconvenience index. Finally, the ASHRAE 140 standard building is used as a case and the proposed scheduling approach is evaluated under two scenarios of working and nonworking days. The proposed scheduling approach can effectively shave the peak load to off-peak load time, reduce electricity bills, and meet the occupants’ comfort.

This paper classifies and discusses the energy flexibility improvement strategies for demand responsive control in grid-interactive buildings based on a comprehensive study of the literature. Both supply and demand sides are considered. The flexibility measures range from renewable energy such as photovoltaic cells (PV) and wind to heating, ventilation, and air conditioning (HVAC) systems, energy storage, building thermal mass, appliances, and occupant behaviors. Currently, owing to the highly developed smart appliances and sensing communication techniques, DR is considered as an essential measure for improving energy flexibility in buildings without much additional investment. With the help of advanced demand response (DR) control strategies and measures, buildings can become more flexible in terms of power demand from the power grid. In this way, buildings achieve a better ability to balance differences in energy supply and demand. Furthermore, a synergistic approach with various measures is advisable, e.g., the use of energy storage technologies with PV and passive DR methods. This paper summarizes the measures for improving the flexibility of commercial and residential buildings, and develops a systematic methodology framework to evaluate energy demand flexibility in buildings.

With the development of data-driven models, extracting information from historical data for better energy forecasting is critically important for energy planning and optimization in buildings. Feature engineering is a key factor in improving the performance of forecasting models. Adding load pattern labels for different daily energy consumption patterns resulting from different time schedules and weather conditions can help improve forecasting accuracy. Traditionally, pattern labeling focuses mainly on finding a day similar to the forecasting day based on calendar or other information, such as weather conditions. The most intuitive approach for dividing historical time-series load into patterns is clustering; however, the pattern cannot be determined before the load is known. To address this problem, this study proposes a novel short-term load forecasting framework integrating an early classification algorithm that uses a stochastic algorithm to predetermine the load pattern of a forecasting day. In addition, a hybrid multistep method combining the strengths of single-step forecasting and recursive multistep forecasting is integrated into the framework. The proposed framework was validated through a case study using actual metered data. The results demonstrate that the early classification and proposed labeling strategy produce satisfactory forecasting accuracy and significantly improve the forecasting performance of the LightGBM model.

Traditional rural energy sources, such as straw, firewood, and coal are the main energy resources in developing countries; however, these resources are associated with low efficiency and can cause considerable air pollution. With the rapid development of renewable energy worldwide, existing energy frameworks in rural areas need to be urgently transformed. Developing a universal and reliable dynamic modeling framework for multi-source heat pumps remains an unresolved issue. To this end, this paper proposes an integrated energy system based on a solar-assisted ground source heat pump (SGSHP), which can facilitate the utilization of renewable energy, reduce the electricity consumption, and provide demand response (DR) resources in rural houses. A 150-m2 rural house on the outskirts of Shanghai, China was considered as a case building. A novel Dymola modeling framework of an SGSHP system was established, and the heating performance was analyzed. Considering the variation in the energy demand in winter, four practical operation modes were implemented to maximize energy efficiency. The results show that the coefficients of performance of the system are 4.2 and 3.5 with and without solar collectors, respectively. The contributions of solar energy, geothermal heat, and electricity in the system are 27%, 18%, and 55%, respectively. Moreover, approximately 79.6% of AC loads can be shaved during evening peak load time in our proposed energy system.

Electricity demand response (DR) improves the overall energy management efficiency and allows for the integration of large-scale renewable energy into the power grid through interactive management and control of the supply and demand sides. However, in China and other emerging countries (e.g., Japan and Australia) with DR programs, the DR market mechanism is not well-established. This is particularly the situation in countries where the state power system is not freely open to participate in the DR market. Previous research has proven that considerable DR resources are largely existing in the demand side; however, the dearth of a market mechanism hinders the development of DR. Hence, a feasible market mechanism is urgently required. In this study, first, the experiences in existing DR-developed markets where DR has been legally regarded as an equivalent electricity resource are investigated. Second, a pilot DR program in Shanghai representing emerging DR markets with a non-liberated electricity background is presented. Moreover, two market mechanisms are analyzed: the energy efficiency obligation mode and the electricity capacity trading mode. Finally, five feasible DR mechanisms—mandatory energy-saving, cap and trade, DR-tiered electricity tariff, price-based program, and economic and emergency DR—are proposed for China and other DR emerging countries.

A knowledge of soil permeability is essential to evaluate hydrologic characteristics of soil, such as water storage and water movement, and soil permeability coefficient is an important parameter that reflects soil permeability. In order to confirm the acceptability of the one-dimensional horizontal infiltration method (one-D method) for simultaneously determining both the saturated and unsaturated permeability coefficients of loamy sand, we first measured the cumulative infiltration and the wetting front distance under various infiltration heads through a series of one-dimensional horizontal infiltration experiments, and then analyzed the relationships of the cumulative horizontal infiltration with the wetting front distance and the square root of infiltration time. We finally compared the permeability results from Gardner model based on the one-D method with the results from other two commonly-used methods (i.e., constant head method and van Genuchten model) to evaluate the acceptability and applicability of the one-D method. The results showed that there was a robust linear relationship between the cumulative horizontal infiltration and the wetting front distance, suggesting that it is more appropriate to take the soil moisture content after infiltration in the entire wetted zone as the average soil moisture content than as the saturated soil moisture content. The results also showed that there was a robust linear relationship between the cumulative horizontal infiltration and the square root of infiltration time, suggesting that the Philip infiltration formula can better reflect the characteristics of cumulative horizontal infiltration under different infiltration heads. The following two facts indicate that it is feasible to use the one-D method for simultaneously determining the saturated and unsaturated permeability coefficients of loamy sand. First, the saturated permeability coefficient (prescribed in the Gardner model) of loamy sand obtained from the one-D method well agreed with the value obtained from the constant head method. Second, the relationship of unsaturated permeability coefficient with soil water suction for loamy sand calculated using Gardner model based on the one-D method was nearly identical with the same relationship calculated using van Genuchten model.

Demand response is an efficient method to flatten the demand curves of end-use customers. This article studies the feasibility of an adsorption heat pump in the demand response of a residential building under winter operating conditions. Stratified storage is introduced into the stratified heat pump system to realize heat recovery, which is also used as a buffer energy source when power shortages occur. This article studies the performance of an adsorption heat pump when the system disconnects the external energy source to simulate the situation of a demand response event occurring through experiments. Moreover, the heating loads of a typical residential building are obtained from the simulations on EnergyPlus. Two day types are selected to evaluate the demand response performance of the system in different situations. The coolest day presents an extreme situation, and the design day represents a normal situation. The demand response potential of the adsorption heat pump is estimated by comparing the heat...

Heating, ventilation, and air conditioning (HVAC) systems, combined with the internal thermal mass of buildings, have been deemed to be promising means of providing demand response (DR) resources, particularly for buildings with active energy storage systems. DR resources, such as peak-load reduction potential, can provide grid-responsive support resulting in a high degree of grid involvement and high flexible electricity demand. In the DR field, the potential of HVAC load flexibility has been considered in buildings. In the future smart buildings, it is important to take advantage of demand-side resources to achieve real-time energy supply–demand balance sustainably. In this context, DR potential and characteristics of buildings play a pivotal role in DR programs. However, few studies have investigated the internal thermal mass’s heat release and DR characteristics of buildings. Thus, a systematic experiment is conducted to study the DR potential and characteristics of internal thermal mass and active storage systems. The DR resources include the passive cooling storage from furniture, building envelope and an active water storage tank. Two DR control strategies, including pre-cooling and temperature resetting, are analyzed in this study. The experimental results show that the strategies are effective for short-term (0.5 h) and intermediate-term (2 h) DR programs. For a long-term DR program, active energy storage technology such as a water storage tank is required to satisfy the occupant's comfort requirements. Hence, we conclude that passive thermal mass and active storage systems should be simultaneously considered in practical DR programs for better DR implementation.

Abrupt salt intrusion in municipal wastewater treatment plants has triggered serious disturbances and deteriorated the biological treatment process from steady state into unsteady state. The effects of sodium (Na+) concentration on the structure and properties of activated sludge during the shock period were investigated in this paper. A floc disintegration characterized as the decreased floc size and increased porosity in the floc matrix was found when excess Na+ was added to the bioreactor. Increased Na+ resulted in a slight decrease in the normalized capillary suction time. About 53–57% of the total extracellular polymeric substances (EPS) derived from activated sludge was protein, at Na+ concentrations

Electric demand flexibility in buildings has been deemed to be a promising demand response resource, particularly for large commercial buildings, and it can provide grid-responsive support. A building with a higher electricity flexibility potential has a higher degree of involvement with the grid response. If the electricity flexibility potential of a building is known, building operators can properly alleviate peak loads and maximize economic benefits through precise control in demand response programs. Previously, there was no standard way to quantify electricity flexibility, and it was difficult to evaluate a given building without experiments and tests. Thus, a systematic approach is proposed to quantify building electricity flexibility. The flexibility contributions include building thermal mass; lights; heating, ventilation, and air conditioning (HVAC) systems, and occupant behaviors. This proposed model has been validated by the instantiation of an office building case on the Dymola platform. For a typical office building, the results show that the electricity flexibility resource not only comes from the HVAC system, but also thermal mass and occupant behavior to a large degree, and buildings with energy flexibility can cut down much of their load during peak load time without compromising on the occupant's comfort.

A building heating, ventilation, and air-conditioning (HVAC) system consumes large amounts of energy. Energy consumption prediction is an effective strategy for operation optimization and energy management in a building. The energy consumption of an HVAC system in a building is influenced by many factors, such as weather conditions, building usage, and thermal performance. However, it is impractical to consider all factors for predicting energy consumption. In this paper, a simplified data-driven model is proposed for predicting the energy consumption of an HVAC system in a building. A novel feature transformation method is introduced to select the most relevant features. Three input features (i.e., degree-day, day type, and month type) are finally adopted in this model. Compared to models developed in previous studies, this simplified model largely reduces the computation time and is easier to operate. The cross-validated root mean square error of this method for cooling energy prediction is less than 20%, indicating its suitability for use in engineering applications.

The Bowen ratio energy balance method often produces extremely inaccurate magnitudes of the flux due to resolution limits of the instruments. We analysed the criteria used for rejecting inaccurate data observed using a Bowen ratio system and the resolution limit of the sensors to analytically determine the reliable values of the Bowen ratio (β) and the latent and sensible heat fluxes. The formula used to calculate the error limit of the Bowen ratio (β) was corrected based on the theory of error analysis. An example was proposed for the common case with 0.2 °C resolution limit of temperature measurement and 0.08 kPa resolution limit of water vapour pressure measurement, to show the steps of accepting or rejecting data observed by a Bowen ratio system. The acceptance or rejection of data observed by a Bowen ratio system is a dynamic process, which should be performed based on the excluded interval of the Bowen ratio and the qualitative relationships among the data observed by a Bowen ratio system. The excluded interval of the Bowen ratio can be structured based on the accuracy of the sensors used. Data are excluded first if they do not satisfy the qualitative relationships between the vapour pressure difference, the temperature difference, Bowen ratio, and the available energy, whereas the data in the rejection region range of the Bowen ratio are excluded second. It is necessary to improve the accuracy of the temperature and humidity probes to improve the acceptance rate for data collected using the Bowen ratio system, apart from improving the observed precision of available energy. Copyright © 2013 John Wiley & Sons, Ltd.