Energy-efficient System Design Research Articles

Enhancing Hydrogels with Quantum Dots

This manuscript explores the interdisciplinary integration of quantum dot–hydrogel composites and smart materials and their applications across a spectrum of fields, including biomedical engineering, environmental sensing, and energy harvesting. It covers the synthesis of novel materials like fluorescent hydrogel nanocomposites that display enhanced chemical stability, mechanical strength, and thermal resistance, highlighting their utility in environmental monitoring and catalysis. In the biomedical sector, innovations include hydrogel composites for targeted drug delivery and advanced therapies such as photothermal DNA hydrogels for tumor treatment. This review also discusses the application of these materials in imaging, diagnostics, and the development of smart sensors capable of detecting various biological and environmental changes. Its scope further extends to optoelectronics and the design of energy-efficient systems, underscoring the versatile functionalities of hydrogels in modern technological applications. Challenges remain in scaling up these technologies for commercial use and ensuring their long-term stability and safety, necessitating future research focused on sustainable, scalable solutions that can be integrated into existing systems.

Electromagnetic–thermal–mass transport triple hybrid model for energy-efficient hydrogen release from metal particles by induction heating

Hydrogen storage in metals is anticipated to be a highly promising technical approach for managing hydrogen in diverse energy applications, emphasizing the need to establish efficient operating conditions. In this study, we developed a numerical model that can simultaneously calculate hydrogen and heat transport combined with electromagnetic induction heating of metal particles. Using the developed numerical simulator, we investigated the behavior of the hydrogen release process from the hydrogen-absorbing metal and proposed important indicators for the operation. The fractions of the electromagnetic energy absorbed by the metal particle used for the hydrogen release, sensible heat, interfacial heat conduction, and thermal radiation were systematically evaluated. Considering the trade-off between temperature rise and the hydrogen concentration gradient, an optimal diameter of metal particles existed for the maximum hydrogen release rate. Similarly, the trade-off between temperature rise and energy consumption revealed an optimal electromagnetic power density for the heat utilization fraction for hydrogen release. Our electromagnetic–thermal–mass transport triple hybrid model constitutes a useful numerical simulator for the design of energy-efficient hydrogen storage systems.

Tuning the Dynamic Thermal Parameters of Nanocarbon Ionanofluids: A Photopyroelectric Study

The present work delineates the tailoring of the thermal effusivity and diffusivity of the novel class of heat transfer fluids—ionanofluids—by the incorporation of nanocarbons like diesel soot (DS), camphor soot (CS), carbon nanotubes (CN), and graphene (GR). When the thermal diffusivity delivers information on the thermal energy propagation, the thermal effusivity concerns the energy exchange at the interface, enabling energy-efficient thermal system design. The nanocarbons are subjected to morphological characterisation by field emission scanning electron microscopy. Fourier-transform infrared and Raman spectroscopic analyses confirm functional groups and vibrational bands. The microcrystalline size and graphiticity are also understood from the Raman spectrum. Ionanofluids prepared by dispersing nanocarbons into an ionic liquid base 1-Butyl-3-methylimidazolium methyl sulfate (BMMS) are analysed by nondestructive photopyroelectric calorimetry (PPE). The PPE analysis of ionanofluids demonstrates that nanocarbons influence thermal parameters in the base fluid, with soot ionanofluids exhibiting increased thermal effusivity and diffusivity due to their various carbon allotropic composition. This study underscores the importance of selecting the appropriate carbon allotrope for tailoring ionanofluids’ thermal properties, providing insights into manipulating these properties for enhanced performance across various industrial applications.

Development of constitutive relations for predicting film boiling crisis in bare and inner wall coated cryogenic tubes with a low-thermal conductive layer for heat transfer enhancement

Closure models for transient cryogenic quench flow boiling heat transfer prediction are finding significant attention to support the design of energy-efficient, cost-effective, and reliable cryogenic fluid management systems. In this regard, the characterization of the film boiling crisis, which indicates the beginning of transient wetting of the wall by liquid, is essential due to the significant heat transfer change past this stage. In the current work, a new rewetting database is developed from 112 chill-down experiments conducted using LCH4, LOX, LAr, and LN2 in feed lines having 0.11 m to 11 m length, 0.4 cm to 2.2 cm inner diameter, 0.5 mm to 5 mm wall thickness, and low-thermal conductive coating thickness up to 157 μm, under several pipe orientations. Additionally, the dataset comprises a mass flux from 10.5 kg/m2s to 1805 kg/m2s, pressure from 109.8 kPa to 1153.8 kPa and gravitational acceleration from terrestrial condition to ±0.01 g. Subsequently, 30 existing seminal rewetting correlations are analyzed for their applicability to transient cryogenic rewetting prediction. Moreover, the importance of feed line and flow parameters in this phenomenon is also studied. Accordingly, a new correlation for rewetting temperature is proposed with 4.15% mean absolute percentage error (MAPE). Further, applying a low-thermal conductive coating to the feed line inner wall surface has already been proven to enhance the chill-down efficiency up to 80%. For modeling such feed systems, determining bulk wall rewetting point is necessary. Hence, a new apparent rewetting temperature correlation to characterize the film boiling crisis in cryogenic coated tubes is proposed for the first time with a MAPE of 4%. Finally, the paper presents the predictions from a non-homogeneous two-phase thermal-hydraulic code, employing the previously reported film boiling correlations and the rewetting correlations from the present work. The obtained model performance indicates considerable improvement in prediction while using the proposed closure models. This shows their potential to support optimization tasks to achieve higher chill-down efficiency.

A Comprehensive Study on the Effects of Surface Roughness on Power Consumption and Heat Transfer Performance in Novel In-Tube Condensation r123yf Refrigerant Systems

This study investigates the impact of surface roughness on the condensation Heat Transfer Coefficient (HTC) of R123yf refrigerant in a uniquely designed test rig with pre-condenser and post-condenser for quality regulation. In mining industries, the mining equipment consumes more amount to power for the Air Conditioning system. To reduce the power consumption of copper metal inside the surface morphology needs to be changed. Experiments were conducted in a 750 mm long, 8.4 mm internal diameter copper tube, with regard to mass flux varying from 150 kg.m-2.s-1 to 300 kg.m-2.s-1, refrigerant quality varying from 0.3 to 0.8, and saturated temperature from 35°C to 45°C. The impact of varying surface roughness (1.5 μm, 2.5μm, 3.4 μm, and 6.7 μm) on HTC was examined. The plane tube condensation experimental results agreed with M M Shah's heat transfer coefficient correlations, with a 20% absolute mean deviation. It was observed that increasing surface roughness enhanced the HTC. The optimal surface roughness was determined to be 3.4 μm, as it resulted in a significant increase in HTC (26.25%) with a moderate rise in power consumption (15.40%). Higher surface roughness led to a drastic increase in power consumption, making it less desirable for practical applications. Through a systematic analysis of the experimental data, this study identifies the critical trade-off between surface roughness and power consumption, providing guidance for the design of energy-efficient condensation heat transfer systems using R123yf refrigerant. By pinpointing an optimal surface roughness for copper tubes used in refrigeration, this study offers a pragmatic solution for enhancing the efficiency of air conditioning systems in mining equipment, a sector notorious for high energy expenditures. The findings indicate a direct application in mining operations where equipment cooling demands contribute significantly to energy consumption. Implementing the recommended surface modifications can lead to substantial energy savings, thereby reducing operational costs and improving the sustainability of mining activities. Furthermore, the adaptation of R123yf refrigerant systems with optimized surface roughness could serve as a model for energy conservation measures across various facets of the mining industry..

Memristors in Cellular-Automata-Based Computing:A Review

The development of novel hardware computing systems and methods has been a topic of increased interest for researchers worldwide. New materials, devices, and architectures are being explored as a means to deliver more efficient solutions to contemporary issues. Along with the advancement of technology, there is a continuous increase in methods available to address significant challenges. However, the increased needs to be fulfilled have also led to problems of increasing complexity that require better and faster computing and processing capabilities. Moreover, there is a wide range of problems in several applications that cannot be addressed using the currently available methods and tools. As a consequence, the need for emerging and more efficient computing methods is of utmost importance and constitutes a topic of active research. Among several proposed solutions, we distinguish the development of a novel nanoelectronic device, called a “memristor”, that can be utilized both for storing and processing, and thus it has emerged as a promising circuit element for the design of compact and energy-efficient circuits and systems. The memristor has been proposed for a wide range of applications. However, in this work, we focus on its use in computing architectures based on the concept of Cellular Automata. The combination of the memristor’s performance characteristics with Cellular Automata has boosted further the concept of processing and storing information on the same physical units of a system, which has been extensively studied in the literature as it provides a very good candidate for the implementation of Cellular Automata computing with increased potential and improved characteristics, compared to traditional hardware implementations. In this context, this paper reviews the most recent advancements toward the development of Cellular-Automata-based computing coupled with memristor devices. Several approaches for the design of such novel architectures, called “Memristive Cellular Automata”, exist in the literature. This extensive review provides a thorough insight into the most important developments so far, helping the reader to grasp all the necessary information, which is here presented in an organized and structured manner. Thus, this article aims to pave the way for further development in the field and to bring attention to technological aspects that require further investigation.

Melting of N-eicosane-based composite phase change materials for thermal energy storage application: A computational analysis in a square cavity

The present numerical study examines the thermal performance of composite n-eicosane phase change material (CPCM) with the addition of different nanoparticles such as Al2O3, Cu, Cuo, and GnP, identifying them as CPCM 1, CPCM 2, CPCM 3, and CPCM 4. This study focuses on the melting behavior of CPCMs with concentration ranges of 2, 5, 8, and 10 wt% in a square encapsulated (SE) geometry aimed at designing an energy-efficient CPCM-based thermal energy storage (TES) system for solar photovoltaic (SPV) applications. Mass fraction contours showed that heat flux at higher concentrations (8 and 10 wt%) contributed to a strong solid-liquid interface, which makes the melt front too wide at all CPCMs. Altogether, the addition of GnP in CPCM (CPCM 4) caused enhancement in thermal conductivity and buoyancy effect, leading to earlier completion of the melting than other CPCMs, irrespective of the concentrations. In addition, the 20–30 % reduction in total time with CPCM 4 over the other three CPCMs at high concentrations of 10 wt% With the influence of nanoparticles, the energy storage capacity (ESC) of CPCMs increased by about 10 %, with concentrations ranging from 2 to 10 wt%. In addition, the variation in total energy release rate between CPCM 2 and CPCM 3 was found to be less significant. However, the ESC of CPCM 4 is 8.5 %, 11 %, and 13 % higher than that of CPCM 1, CPCM 2, and CPCM 3, respectively. With the influence of the inherent thermal properties of GnP, the better thermal performance achieved by CPCM 4 confirms its suitability for SPV system designs. Study provides insights into the design of energy-efficient CPCM-based TES systems for SPV applications.

Study of the combined solar heating system of residential houses

The use of renewable energy sources in the heat supply systems of residential houses is one of the urgent issues today. Since solar energy has the highest potential among renewable energy sources, it is widely used in residential heat supply systems. Although solar energy is used in heating systems until now, due to the large number of factors affecting the heating system, research in this field is accelerating. In this research work, a combined scheme for using solar energy in the heating system of residential houses is proposed and the results of pilot studies conducted in the season from November 2020 to February 2021 in the heating system implemented according to this scheme are presented. According to the results of the research, it is possible to cover up to 70% of the heat load in the heating system of residential houses. The information presented in the research work can be used in the design and implementation of energy-efficient solar heating systems.

Designing a new bell-type primary air nozzle for large-scale circulating fluidized bed boilers

The design of energy efficient engineering systems is crucial for sustainable operation when economic and environmental consequences are considered. Circulating Fluidized Bed (CFB) boilers, which are among the major contributors to world electricity production, are still increasing in numbers and unit sizes. Primary air nozzles are key components of CFB boilers that may decrease energy consumption and increase energy efficiency, and they need to be carefully designed. There are certain types of nozzles commonly used in the air distribution grate, but even minor design improvements on the nozzle can significantly decrease the pressure loss. This work is about optimizing the bell-type primary air nozzle used in the Turkish lignite-fired ÇAN Thermal Power Plant (CTPP), which has two 160 MWe CFB boilers, through computational fluid dynamics (CFD). Initially, the bell-type nozzle was designed newly by changing the inner head holes geometry. After that, the nozzle geometry was optimized by changing the orifice size and angle to decrease the pressure drop, increase the orifice velocity outlet, and flow uniformity through CFD simulations. With the optimum nozzle geometry, the velocity at the outlet orifices was increased, and a decrease of 2.86 kPa was achieved in the total pressure loss. Furthermore, when the nozzle orifices were designed downwardly with an angle of 105°, pressure drop across the nozzle decreased by 7.6 %, and the uniformity index increased by 2 % at the outlet orifices. Using the bell-type primary air nozzle, which is newly designed, in the CTPP boiler not only will save 2.26 GWh/year of energy consumption but also minimize the backflow risk in the boiler operation.

A new thermal comfort model based on physiological parameters for the smart design and control of energy-efficient HVAC systems

Indoor thermal comfort represents a key aspect of building design. The reference standards do not consider the thermal adaptability of the human body, and HVAC system control strategies are based on a steady-state assumption that returns an incorrect estimate of occupants' thermal demand with a consequential misleading of the building energy consumption and of system sizing. To overcome these issues, a physiological thermal comfort model for the human body thermal behaviour evaluation is developed in MatLab environment for assessing the dynamic variation of the physiological parameters and for characterizing the occupants’ thermal sensation. Finally, the developed human body multi-node model is implemented in a building energy simulation tool (called DETECt 2.4) to perform three proposed strategies for the dynamic control of the building thermo-hygrometric parameters of the building and of the corresponding heating and cooling demands. These strategies provide an hourly regulation of relative humidity and air temperature by means of a two-step optimization that maximizes the thermal comfort of the occupants and minimizes energy consumption. To show the potentiality of the developed model, a suitable case study consisting of an office space is considered. Here, space heating and cooling demands obtained by applying the novel developed model are compared to those obtained through standard set-point values of air temperature and relative humidity (20 °C, 45% for heating needs, and 26 °C, 50% for cooling ones). By the comparison, between the proposed model – which considers the optimal hourly set point assessing the occupant in thermal evolution – and the reference ones, interesting results are obtained. Generally, a higher consumption is achieved by considering the proposed comfort strategies (from 2 to 16%), representing the price to be paid to maximize the comfort of the occupants and to annul the 3650 h of discomfort of the reference case.

Design of energy-efficient ionic liquid-based extractive distillation systems for ethanol dehydration including alternatives for ionic liquid recovery

Designs of extractive distillation systems for ethanol-water separation using ionic liquids as entrainers are presented. Distillation sequences that integrate the extractive column with five options for ionic liquid recovery were designed. Two types of ionic liquids, namely, 1-butyl-3-methylimidazolium chloride [BMIM](Cl)] and 1-ethyl-3-methylimidazolium tetrafluoroborate [EMIM](BF₄)], were considered. Once initial designs were obtained, simulations using the Aspen Plus environment were conducted to identify the operating conditions of the separation sequences that minimize energy consumption. The designs were tested under two levels of IL flows, one with the minimum flow required for the separation and another one with the flows that minimized the total annual cost of the extractive column. From the total of 20 design options, it was found that the most energy efficient design was based on a low flow of [BMIM(Cl)] as entrainer, with an extractive column followed by a desorption column and a membrane unit for IL recovery.

Systems of social practice and automation in an energy efficient home

The development of residential automation and energy management systems have aimed to achieve energy reduction within the home. These systems have been developed to compliment human behaviour and potentially impart change in the way people consume energy. The development of energy efficient buildings has been considered a sustainable approach to better manage or optimise energy consumption and generation within a building however, multiple studies have demonstrated some limitations to these buildings and systems. The advancement of the home system of practice using the basis of Social Practice Theory has demonstrated a new focus for the design methodology of these systems. The home system of practice outlines the routines and repetitive nature of individual lifestyles, and these routines result in the temporal characteristic of energy consumption. This study monitored an Australian home that consisted of renewable energy systems, smart technology and automated systems designed to reduce the use of grid electricity. The aim was to understand the performance of the automation systems and interaction with the occupants and their routines. The paper discusses the effectiveness of incorporating social theories and the home system of practice into the design of energy efficient buildings and energy management systems. The methodology utilised machine learning techniques to identify patterns in energy consumption data and related these patterns to the routines and lifestyles of the home occupants. These patterns aimed to describe why the automation system incorporated into the study home did not operate as intended and how design changes can increase effectiveness and performance.

Research on the Use of Machine Learning on Building Facades

Artificial intelligence and its sub-branch, machine learning technologies, have developed rapidly in recent years and their use for various purposes has seemed to be increased in various sectors from automotive to medicine, from law to marketing. Similarly, these technologies have begun to be used in the building sector and in the field of architecture. These technologies are being used in many fields in architecture such as feasibility studies, building design, project control, occupational safety, earthquake resistant building design and applications, energy efficient system design, construction with smart construction equipment, smart building design, and smart facade design. Despite this increasing use in the field, it has been determined by the literature review that the number of studies focusing on the use of machine learning in architecture, especially on building facades, is low. In this sense in the study, it is aimed to examine the relationship between artificial intelligence and machine learning technologies with architecture in the context of building facades. Initially in the study the topics and the historical process related to artificial intelligence and machine learning were explained, subsequently the use of technologies on the building facades was examined through examples. In this way, a guiding resource has been created for those who want to work on this subject in the future.

Energy Efficient Outdoor Lighting System Design: Case Study of IT Campus

Outdoor lighting solutions are a key to safe urbanization. It is important that assessment of lighting is done at the design stage keeping in mind the crucial parameters like environment friendly design, light pollution, and energy efficiency. These crucial parameters are met by meticulously using lighting standards at each and every stage of lighting design. This process further naturally inclines in realizing sustainable lighting solutions for the future generations. In this paper, a case study of an Information Technology (IT) campus which requires suitable outdoor lighting system is considered. Outdoor lighting is very essential from the security perspective and also for the people and vehicle movement during night time. Hence it is necessary to design and implement an effective lighting scheme. To achieve this it is necessary to perform extensive lighting calculations and simulations in DIALUX software platform.

Stochastic Computing in Beyond Von-Neumann Era: Processing Bit-Streams in Memristive Memory

Stochastic Computing (SC) is an alternative computing paradigm that promises high robustness to noise and outstanding area- and power-efficiency compared to traditional binary. It also enables the design of fully parallel and scalable computations. Despite its advantage, SC suffers from long latency and high energy consumption compared to conventional binary computing, especially with current CMOS technology. The cost of conversion between binary and stochastic representation takes a significant cost with CMOS circuits. In-Memory Computation (IMC) is introduced to accelerate Big Data applications by removing the data movement between memory and processing units, and by providing massive parallelism. In this work, we explore the efforts in employing IMC for fast and energy-efficient SC system design. We specially focus on memristors as an emerging technology that promises efficient memory and computation beyond CMOS. We discuss the potentials and challenges for realizing efficient SC systems in memory.

Protection of Three Phase Induction Motor Using Embedded System

This paper present a PIC microcontroller – based control system for the protection of a three phase induction motor. The use of microcontroller technology has enabled the design of energy efficient and cost effective reliable control systems for induction motors. Fault types of induction motor like unbalanced voltage, over voltage, under voltage, over current, phase failure, over heat and more considered in this work. Fault monitoring and diagnosis are performed using protest environment. Fault classification is achieved through the microcontroller which includes a program for fault classification. When the fault occurs, the microcontroller sends a signal to the interfaced digital relay to trip the motor circuit and another signal to an LCD to display the type of fault. The use of microcontroller reduce the response time of the protection system and make it more suitable for real time operation. The proposed protection scheme is simulated using MATLAB Simulink. MATLAB simulation results show that the well trained protest scheme is able to detect all types of internal faults at different locations. The microcontroller used in this work is the high performance enhanced flash PIC16F877A Microcontroller of microchip which has an on chip analogue to digital converter peripheral, among other features. Keywords: PIC microcontroller, three phase induction motor, fault classification, Proteus environment.

Short-Packet Amplify-and-Forward Relaying for the Internet-of-Things in the Face of Imperfect Channel Estimation and Hardware Impairments

In next-generation wireless systems ultra-reliable low-latency communications (URLLC) have to be realized in support of the Internet-of-things (IoT). However, this is quite a challenge in the face of channel estimation errors (CEEs) and hardware imperfections (HWIs). Hence, we consider a variety of realistic HWIs as well as CEEs and evaluate the average block error rate (BLER) of a short-packet based cooperative amplify-and-forward (AF) relaying network. Our simulation and analytical results reveal that as expected, both the CEEs and HWIs lead to a substantial average BLER degradation. In particular, CEEs lead to a BLER floor, which is further aggravated by the increase in HWIs. A high level of HWIs results in a BLER tending to one, regardless of the transmit power. Furthermore, it is shown that the CEEs and HWIs gravely degrade the energy efficiency of the idealized perfect scenario. This observation shows that both the CEEs and HWIs constitute critical issues in the design of energy efficient communication systems. However, through solving the optimization problems formulated, we conceived several schemes for mitigating the degradations imposed by the CEEs and HWIs, e.g., in our adaptive-duration training scheme the total CEE of the hops is shared in line with the current status of the two channels. Our simulation results show that this scheme significantly reduces the BLER and mitigates the deleterious effects of CEE.

Dielectric engineering enable to lateral anti-ambipolar MoTe 2 heterojunction

Atomically two-dimensional (2D) materials have generated widespread interest for novel electronics and optoelectronics. Specially, owing to atomically thin 2D structure, the electronic bandgap of 2D semiconductors can be engineered by manipulating the surrounding dielectric environment. In this work, we develop an effective and controllable approach to manipulate dielectric properties of h-BN through gallium ions (Ga+) implantation for the first time. And the maximum surface potential difference between the intrinsic h-BN (h-BN) and the Ga+ implanted h-BN (Ga+-h-BN) is up to 1.3 V, which is characterized by Kelvin probe force microscopy. More importantly, the MoTe2 transistor stacked on Ga+-h-BN exhibits p-type dominated transfer characteristic, while the MoTe2 transistor stacked on the intrinsic h-BN behaves as n-type, which enable to construct MoTe2 heterojunction through dielectric engineering of h-BN. The dielectric engineering also provides good spatial selectivity and allows to build MoTe2 heterojunction based on a single MoTe2 flake. The developed MoTe2 heterojunction shows stable anti-ambipolar behaviour. Furthermore, we preliminarily implemented a ternary inverter based on anti-ambipolar MoTe2 heterojunction. Ga+ implantation assisted dielectric engineering provides an effective and generic approach to modulate electric bandgap for a wide variety of 2D materials. And the implementation of ternary inverter based on anti-ambipolar transistor could lead to new energy-efficient logical circuit and system designs in semiconductors.

Coordinated Optimization for Energy Efficient Thermal Management of 5G Base Station Site

5G mobile communication system achieve better network performance while causing a significant increase in energy consumption, which hinders the sustainable development of the telecom industry. Even with many efforts for energy efficient system designs and equipment operation are developed, there is still a plenty of potential for energy savings in HVAC operation of 5G base station site since a significant amount of energy is consumed for thermal management by the HVAC system to control the indoor environment within an acceptable temperature range for safe and reliable operation of the base station (BS) equipment. In this work, a coordinated optimization approach for energy efficient thermal management of 5G BS site is proposed. The approach collaboratively optimized the HVAC system and the BS equipment with MILP model. The application results show that the average energy costs savings in HVAC operation with the coordinated approach are 24.8%-32.5%, and the total BS site costs savings are more than 13%.

Robust and Energy-Efficient Hardware: The Case for Asynchronous Design

The current technologies behind the design of semiconductor integrated circuits allow embedding billions of components in a singe silicon die, enabling the construction of very complex circuits in a tiny space, dissipating little energy and producing huge amounts of useful computational work. However, the current levels of integration for electronic components in silicon and similar materials are not easily managed, as parameter variations grow steadily, making the design tasks increasingly challenging. Synchronous techniques have dominated the digital system design landscape for many decades, but their costs are increasingly hard to cope with. Asynchronous design and particularly quasi-delay insensitive design promises to deal with the same challenges more gracefully in current advanced nodes, and possibly irrevocably in future technology nodes. This article proposes a review of the state of the art in using asynchronous circuit design techniques to achieve energy-efficient and robust digital circuit and system design. In particular, the definition of a robust digital circuit comprises addressing several aspects to which a digital system design is expected to be robust to, including: (1) voltage variations; (2) process variations; (3) temperature variations; (4) circuit aging. Besides addressing energy-efficiency and all the mentioned robustness aspects, this work also approaches some of the state-of-the-art tools available to deal with asynchronous design, and points to desirable research development to be conducted in these subjects in the future.