4D Printing of Shape Memory Materials for Textiles: Mechanism,Mathematical Modeling,and Challenges

Shape memory materials (SMMs) in 3D printing (3DP) technology garnered much attention due to their ability to respond to external stimuli, which direct this technology toward an emerging area of research, “4D printing (4DP) technology.” In contrast to classical 3D printed objects, the fourth dimension, time, allows printed objects to undergo significant changes in shape, size, or color when subjected to external stimuli. Highly precise and calibrated 4D materials, which can perform together to achieve robust 4D objects, are in great demand in various fields such as military applications, space suits, robotic systems, apparel, healthcare, sports, etc. This review, for the first time, to the best of the authors’ knowledge, focuses on recent advances in SMMs (e.g., polymers, metals, etc.) based wearable smart textiles and fashion goods. This review integrates the basic overview of 3DP technology, fabrication methods, the transition of 3DP to 4DP, the chemistry behind the fundamental working principles of 4D printed objects, materials selection for smart textiles and fashion goods. The central part summarizes the effect of major external stimuli on 4D textile materials followed by the major applications. Lastly, prospects and challenges are discussed, so that future researchers can continue the progress of this technology.     

Plasticizing effect of biodegradable dipropylene glycol bibenzoate and epoxidized linseed oil on diglycidyl ether of bisphenol A based epoxy resin

Major limitation for use of epoxy thermosets in engineering applications is its sudden brittle failure. In the present study dipropylene glycol dibenzoate (DPGDB) based plasticizer is used to modify diglycidyl ether of bisphenol A (DEGEBA) based epoxy resin system via simple blending technique. Bio-based epoxidized linseed oil was also used to modify epoxy resin system and compared with DPGDB modified resin. For DPGDB modified resin storage modulus and loss modulus of the epoxy system modified with 10% plasticizer increased by 7.54% and 12.24%, respectively. The primary mechanism responsible for such behavior is improved crosslinking density. With 5% plasticizer loading, flexural strength increased by 21%. There was an improvement of 312.74% in strain at failure for 10% plasticizer loading, while preserving its mechanical strength. It was found that DPGDB based modification was better than epoxidized linseed oil modification.     

Self-tuning dynamic models of HVAC system components

A great majority of modern buildings are equipped with Energy Management and Control Systems (EMCS) which monitor and collect operating data from different components of heating ventilating and air conditioning (HVAC) systems. Models derived and tuned by using the collected data can be incorporated into the EMCS for online prediction of the system performance. To that end, HVAC component models with self-tuning parameters were developed and validated in this paper. The model parameters were tuned online by using a genetic algorithm which minimizes the error between measured and estimated performance data. The developed models included: a zone temperature model, return air enthalpy/humidity and CO₂ concentration models, a cooling and heating coil model, and a fan model. The study also includes tools for estimating the thermal and ventilation loads. The models were validated against real data gathered from an existing HVAC system. The validation results show that the component models augmented with an online parameter tuner, significantly improved the accuracy of predicted outputs. The use of such models offers several advantages such as designing better real-time control, optimization of overall system performance, and online fault detection.     

Dynamic modelling and simulation of a room with hot water baseboard heater

A dynamic model of a room with a hot water baseboard heater is developed. In the modelling methodology used, a typical finned‐tube baseboard heater with its cover was divided into several control volumes. The mass, energy balance and momentum equations were formulated and solved for each control volume. The dynamic model was used to study the effect of important design and operating parameters on the heat output rate of the baseboard heater. Simulation runs showing the dynamic responses of airflow rates, air temperature from the heater, and hot water temperature are presented. Copyright © 2005 John Wiley & Sons, Ltd.     

Squeeze-film narrow porous journal bearings lubricated with a micropolar fluid

Squeeze-film narrow porous journal bearings using a lubricant containing solid particle additives and characterized as a micropolar fluid were analysed. The load capacity and time of approach increase as the micropolar parameter characterizing the concentration of the microstructure imparted to the lubricant by the additives increases. The load capacity and time of approach decrease as the permeability and/or the thickness of the porous wall increases.     

Density Based Fuzzy C Means Clustering to prolong Network Lifetime in Smart Grids

Wireless sensor networks (WSN's) are preferred for industrial applications due to progressive increase of sensor electronics. One such application is deployment of WSN's in smart grids. Smart Grid integrates information and communication techniques with electricity network. Smart grids utilize sophisticated control and monitoring devices for improving the efficiency of the grid. For energy efficient, low cost monitoring and control in smart grid WSN's is treated as a promising technology. Advanced Metering Infrastructure (AMI) is the key technology in the distribution networks of Smart Grid. The AMI is composed of various sensors for metering purpose. The meter data is also useful for the distribution operators to manage the demand response. The network involves smart meters, smart electric gas and water meters along with digital network management appliances for optimizing the electric network with real time data management. The smart sensors are limited in terms of battery, operational power and memory. These sensors communicate with the base station in restricted range. The communication between smart grid nodes and base station (sink) is multi-hop in nature. The communication takes place within limited range of communication so the security concerns that are involved in the network are to be handled by the routing protocols. So as to make the bidirectional communication efficient between the smart sensors and utility an effective routing scheme is required for these energy limited devices to handle the heavy network traffic in smart grids. Here energy efficient routing for WSN's in NAN networks to attain load balancing is proposed through density based Fuzzy C means clustering (DFCM). The obtained simulation results show that DFCM can provide a satisfactory performance for enhancing the network life span.

     

The dynamic behaviour of squeeze films in one-dimensional porous journal bearings lubricated by a micropolar fluid

The generalized Reynolds equation governing the pressure distribution for a micropolar lubricant in a dynamically loaded porous journal bearing is derived and applied to one-dimensional squeeze film journal bearings operating under a cyclic load. The analysis indicates how the microstructure in the lubricant, the permeability of the bearing material and the bearing wall thickness influence the operating eccentricity ratio.     

Neuro-optimal operation of a variable air volume HVAC&R system

Low operational efficiency especially under partial load conditions and poor control are some reasons for high energy consumption of heating, ventilation, air conditioning and refrigeration (HVAC&R) systems. To improve energy efficiency, HVAC&R systems should be efficiently operated to maintain a desired indoor environment under dynamic ambient and indoor conditions. This study proposes a neural network based optimal supervisory operation strategy to find the optimal set points for chilled water supply temperature, discharge air temperature and VAV system fan static pressure such that the indoor environment is maintained with the least chiller and fan energy consumption. To achieve this objective, a dynamic system model is developed first to simulate the system behavior under different control schemes and operating conditions. A multi-layer feed forward neural network is constructed and trained in unsupervised mode to minimize the cost function which is comprised of overall energy cost and penalty cost when one or more constraints are violated. After training, the network is implemented as a supervisory controller to compute the optimal settings for the system. Simulation results show that compared to the conventional night reset operation scheme, the optimal operation scheme saves around 10% energy under full load condition and 19% energy under partial load conditions.     

Micropolar fluid lubrication of one-dimensional journal bearings

A study of the characteristics of one-dimensional journal bearings shows that the load capacity increases and the coefficient of friction decreases as the parameter $\text{μ}{}_1$, which characterizes the microstructure of the base oil due to the presence of additives, increases. The time of approach increases as the parameter $\text{μ}{}_1$ increases.     

Real‐time tuning of PI controllers in HVAC systems

The problem of tuning single‐loop controllers in heating, ventilating and air conditioning (HVAC) systems is explored. The HVAC process was described by a first‐order‐plus‐dead‐time (FOPDT) model. By using recursive least squares method, the model parameters were updated while the system remained in closed‐loop. The H_∞ loop‐shaping tuning rules published in the literature were transformed to discrete‐time tuning rules and were implemented in an adaptive PI control strategy. The methodology was applied to a discharge air temperature (DAT) control system. The output responses of adaptive PI controller were compared with a LQR optimal adaptive controller. Simulation results show that the adaptively tuned PI controller is able to track setpoint changes very well in the presence of changes in plant parameters, disturbances and external noise acting on the system. Copyright © 2004 John Wiley & Sons, Ltd.