Energy Conservation Model Research Articles

Behavior Modification and Introduction of Voluntary Simplicity Lifestyle toward Organisational Energy and Resource Conservation Practice

The study focused on various energy and resource conservation efforts carried out by employees in response to sustainable-operation initiatives introduced by the organization. The research utilized qualitative research technique to provide the details of aligning productivity improvement measures to energy and resource conservation practice. Giving attention to the response of the employees, the study pointed out the importance of behavior change, and voluntary simplicity lifestyle toward the creation of an energy and resource conservation model. Results suggested the incentivized motivation, and conscious reduction of unnecessary consumption, and voluntary simplicity can have positive environmental and sustainable benefits for the organization.

A Genetic Optimisation Model for Energy Conservation of Circulating Water Pump Station with Variable Speed Pumps

A Genetic Optimisation Model for Energy Conservation of Circulating Water Pump Station with Variable Speed Pumps

A genetic optimisation model for energy conservation of circulating water pump station with variable speed pumps

A genetic optimisation model for energy conservation of circulating water pump station with variable speed pumps

Energy-conservation model of inter-provincial cooperation that accounts GDP and social benefits

With rapid development of the global economy, economic growth is increasingly dependent on energy consumption, and the world faces the associated problems of environmental pollution and depletion of energy sources. This creates a challenge: Our ability to achieve these goals is severely constrained by the current governance based on non-cooperative energy conservation. To improve energy conservation in China, we developed an energy-conservation model based on market mechanisms. The model has three parts: (1) a two-objective (GDP and social benefits) optimization model; (2) a model that determines the optimal trading volume for energy conservation quotas in each province, including division of provinces into quota buyers and sellers and a cooperative game model for energy conservation quotas; and (3) a Nash distribution model for inter-provincial cooperation to fairly distribute the benefits from cooperation. We then used Shandong, Zhejiang, and Jiangsu provinces for an empirical analysis of the cooperative model. With the current territorial management approach, the social benefits of the inter-provincial cooperation based on option trading increased by 2.79 %, and GDP increased by 273.636 × 109 CNY. After a reasonable distribution of the benefits, each province benefited from the cooperation. This demonstrates that our model can improve China's current energy conservation governance.

A 2D energy-conserving contact model for the combined finite-discrete element method (FDEM)

The combined finite-discrete element method (FDEM) has been widely used to simulate the progressive fracturing of brittle materials from continua to discontinua. However, due to the relatively simple definition of contact potential, the contact interaction algorithm utilized in the original FDEM is element size-dependent. As a result, a non-smooth and fluctuating contact force direction can occur when a contact point moves from one area of an element to another, and the contact interaction algorithm may fail to accurately evaluate the tangential contact force. To circumvent these limitations, we adopt an energy-conserving model developed recently to calculate the contact force in 2D FDEM, in which the magnitude and direction of contact force can be directly determined by geometrical features. A suite of numerical benchmarks is conducted to validate the effectiveness and robustness of the proposed method for contact interaction processing between discrete bodies, and the advantages of the proposed method are also demonstrated. As an application, two typical examples are performed to systematically explore the potential of the proposed approach for evaluating the stability of rock mass and rock slope. The proposed contact model may help enhance the applicability and accuracy of FDEM for rock fracturing simulation.

Canopy drag parameterization from field observations for modeling wave transformation across salt marshes

Understanding, quantifying, and predicting wave transformation across marsh vegetation canopies is important for assessing the efficacy of nature-based shoreline strategies. A key challenge for modeling wave dissipation in coastal marshes is accurately representing the canopy drag, particularly as previously proposed canopy drag coefficient (CD) expressions vary considerably for the same vegetation and wave properties. There is also as yet no consensus on which dimensionless parameter best explains the variation of CD with wave conditions and water depth in marshes. This study addressed these challenges using wave, elevation, and vegetation measurements collected at two natural salt marshes across two summers. The dataset was used together with a wave energy conservation model to (i) identify and test possible reasons for differences among previously published CD expressions for salt marshes; and, (ii) derive and test expressions for CD as a function of different dimensionless parameters. We found that uncertainties in measurements of vegetation properties (shoot height, diameter, density) lead to substantial uncertainties in CD expressions, which may explain some differences among previous studies. When plotted versus Keulegan Carpenter number (KC) or Reynolds number (Re), CD values vary by roughly a factor of two for large waves (KC > 100) depending on water depth. When plotted versus Cauchy number (Ca), the ratio of hydrodynamic drag force to the canopy’s elastic restoring force, CD values collapse onto a single curve. We suggest that Ca is the more appropriate parameter for representing CD under larger waves because it represents the force balance relevant for plant motion and recommend future studies to test CD(Ca) relationships for different canopy heights.

Experimental and numerical studies of droplet self-assembly behaviors on hydrophilic/hydrophobic patterned surface

Self-assembled and well-defined fluid patterns of ink droplet deposition are building blocks for printed electronics and next generation of OLED displays. Using surface energy differences created by hydrophobic/hydrophilic patterned (Alt-Wet) surface to propel/retain liquid during the droplet deposition has renewed interests for high resolution printing. In this study, the droplet deposition and split dynamics on the patterned surface have been visualized experimentally. The numerical simulations have revealed that the contact angle contrast (ΔΘ) of the Alt-Wet surface can be as small as 25° to successfully split a droplet by the hydrophobic stripe, providing large enough Reynolds number (Re) for kinetic energy against droplet internal viscous bonding energy holding droplet together. In addition, the droplet splitting, satelliting, and splashing modes are highly influenced by the Alt-Wet surface pattern geometry that governs the stability of liquid diffusion and pressure distribution during the droplet deposition. The derived energy conservation model has theoretically confirmed the experimental and numerical findings that the droplet deposition dynamics are the function of fluid properties and surface wetting characteristics when given Alt-Wet unit. This systematic study on droplet deposition and self-assemble dynamics can provide general design guidance for high resolution ink patterning for printed flexible electronics and micro-fluidics applications.

Characterising the effect of model dormitory on energy-saving intention of college students through the lens of reference points

The demonstration of an energy-conservation model is an important way to increase the energy-saving intention (ESI) of college students. However, the psychological mechanism underlying the effectiveness of such an approach remains unclear, hindering its implementation. This study innovatively elucidates this psychological mechanism from the perspective of reference point (RP). In this study, 125 college students from Xi'an, China, were studied using eye-tracking and a questionnaire with the aim of elucidating the excitation level of RP under the stimulation of different types of energy-saving model dormitories and the corresponding variation in college students' ESI. The relationship between the excitation of the RP and the ESI was then determined using multiple linear regression analysis. Eye-tracking was applied with the aim of measuring the excitation level of the RP, whereas the questionnaire was used to measure the variation in the college students' ESI. The following conclusions were found in this study: (1) Under the stimulation of the energy-saving model dormitory, different RPs were excited to varying degrees. Among the RPs, the group-RP and the negative RP had higher excitation levels; (2) Different types of energy-saving model dormitories affected the ESIs differently. Among the model dormitories, students in the positive low-intensity group exhibited the greatest improvement in ESI; (3) Compared to the group-RP, the excitation of the self-RP had a greater impact on the variation of the college students' ESI, while the pair of ‘positive-negative’ RPs had a smaller impact. The results of the study can help school administrators to effectively develop energy-saving intervention strategies to reduce energy consumption in dormitory buildings.

A transfer-learning-based energy-conservation model for adaptive guided routes in autonomous vehicles

Autonomous vehicles (AV) are expected to improve road safety and reduce traffic congestion by optimizing routes and reducing human errors. AVs have the potential to increase accessibility for people with disabilities and reduce the environmental impact of transportation. AVs require radio transmitters to communicate with other vehicles and infrastructure, external charging to power their electric motors, and communication equipment to receive real-time data about traffic and road conditions. Additionally, these requirements must be met for AVs to operate efficiently and conserve energy. Therefore, this work introduces a novel technique called energy-conservation guided route adaptation (EC-GRA) that aims to enhance the energy efficiency of connected vehicles. With the balance in energy adaptation for distinct purposes, the utilization rate is adjusted for communication and navigation. The complex decisions are confined to the energy availability and conservation factors required in an adaptive driving condition. This technique employs transfer learning to update the available and adaptable energy ratios under displacement-based route adaptations. In the learning process, the transfer and update states for displacement-aware decisions under varying scenarios are modeled. This study validates the state transitions involved in recommending energy utilization during both autonomous and guided driving scenarios. The results show that the proposed methodology exhibits superior performance compared to the currently available techniques. The EC-GRA under consideration has demonstrated an average energy conservation ratio of 45.58. The decision rate for this method is 0.63/navigation, while its energy utilization is 126.37 Joules. The number of failures observed in the proposed EC-GRA is 6/navigation, which represents an improvement over the existing approach.

On the Evolution of, and Hot Gas in, Wind-Blown Bubbles around Massive Stars - Wind Bubbles Are Not Energy-Conserving

The structure and evolution of wind-blown bubbles (WBBs) around massive stars has primarily been investigated using an energy-conserving model of wind-blown bubbles. While this model is useful in explaining the general properties of the evolution, several problems remain, including inconsistencies between observed wind luminosities and those derived using this formulation. Major difficulties include the low X-ray temperature and X-ray luminosity, compared to the model. In this paper, we re-examine the evolution, dynamics, and kinematics of WBBs around massive stars, using published ionization gasdynamic simulations of wind-blown bubbles. We show that WBBs can cool efficiently due to the presence of various instabilities and turbulence within the bubble. The expansion of WBBs is more consistent with a momentum-conserving solution, rather than an energy-conserving solution. This compares well with the dynamics and kinematics of observed wind bubbles. Despite the cooling of the bubble, the shocked wind temperature is not reduced to the observed values. We argue that the X-ray emission arise mainly from clumps and filaments within the hot shocked wind region, with temperatures just above 106 K. The remainder of the plasma can contribute to a lesser extent.

Evaluation of the mid- and long-term effects of a private car driving-restriction policy under the carbon emission peak target.

To investigate the medium- and long-term effects of a driving-restriction policy under the guidance of carbon emission peak goals, Beijing was taken as an example to construct a private-car energy-conservation and emission-reduction model with dual-driving factors from the perspective of the economy, environment, technology, and energy. Through causal analysis, the negative effects of a driving-restriction policy were revealed. The simulation results revealed the following. (1) A driving-restriction policy is effective in the short term, but in the long run, it cannot effectively reduce CO2 emissions and the quantity of fuel used in private cars (e.g., the increase in the amount of CO2 pollution and degree of parking space tension, as well as the rebound of air pollution). (2) Compared with the driving-restriction policy, the combined policy reduces the amount of CO2 pollution by approximately 52.45%, the PM2.5 concentration by 21.98%, and the quantity of fuel in private cars by 33.42% by 2035, while improving the air quality by approximately 144.79%. Therefore, this article provides a theoretical basis for optimizing driving-restriction policies and achieving the carbon emission peak target.

Research on the collision model of high-temperature alumina droplets with cold wall for solid rocket motors

The study on the adhesion and rebound behavior of high-temperature alumina droplets impacting on the cold wall is very meaningful for the accurate prediction of slag deposition and internal flow field in solid rocket motors. In this paper, based on high-temperature alumina droplet impact experimental system, the experiment of alumina droplet impacting on the cold wall was carried out, and the temperature response of alumina droplet during the impact is obtained by the colorimetric thermometry. The study shows that the high-temperature alumina droplets impacting on the cold wall in a certain range of Oh number and Re number exhibit two kinds of behaviors: rebound and adhesion; based on experiments, the distribution laws of rebound and adhesion behaviors of alumina droplets impacting the cold wall are obtained; based on the energy conservation model, and introducing the heat transfer model between the high-temperature droplet and the cold wall, the maximum spreading coefficient model of alumina droplet impact on the cold wall and the prediction model of rebound and adhesion results were established, and the maximum spreading coefficient model prediction results were in good agreement with the experimental data.

Acoustothermal phase change and acoustically driven atomization for cold liquid microthrusters

Over the years, a diverse range of physical and chemical phenomena have been explored and applied to devise reliable, small thrusters for stationkeeping and orientation of spacecraft. Commercial space flight is accelerating this need. Here, we consider acoustically driven melting of a frozen working fluid in the nozzle of an acoustic device, followed by acoustofluidic atomization from the nozzle to produce thrust. Fifty-five MHz acoustic waves generated by piezoelectric transducers couple into liquid and transfer energy in the form of both acoustic radiation and streaming, producing a directed atomized spray. A challenge in this system, as with most liquid-thrust systems, is the risk of phase change due to the extreme thermal environment in space, particularly in the freezing of the working fluid. Though acoustic energy is known to produce rapid and controllable heating, it so far has not been used to produce phase changes. The atomization produces capillary pressure sufficient to draw in fluid from a reservoir, though we do use a simple pressure-driven pump to support greater atomization rates. We provide a simple energy conservation model to explain the acoustothermal interaction and validate this with experiments. The specific impulse and thrust of this type of thruster are quite modest at 0.1–0.4 s and 12.3 μN, respectively, but the thruster component is small, light, and is without moving parts, a fascinating potential alternative to current technologies.

Photoelectron Spectra of Hot Polyatomic Ions: A Statistical Treatment of Phenide.

Many distinct vibrational states contribute to the congested photoelectron spectra of hot polyatomic anions. This often makes the complete Franck-Condon (FC) analysis both impractical and unnecessary. Although it is common to limit the FC calculations to a subset of the FC-active modes, such a limited approach is strictly applicable to the ground-state (cold) anions only. At high temperatures, all vibrational modes participate in thermal excitation, and the FC and thermal activities become intertwined. We report the photoelectron spectra of ∼700 K phenide (C6H5-) obtained at 355 nm (3.49 eV), 532 nm (2.33 eV), and 611 nm (2.03 eV) and describe several practical models that help interpret and analyze the results. Among them are the active-modes model, the active modes + dark bath and the active modes + bright bath models, and, finally, the energy-conservation model. The models combine the results of limited (and, therefore, feasible) FC calculations with statistical analysis and provide efficient means of determining the ion temperature from the broad and congested photoelectron spectra. The described capability can be applied to hot plasmas, the collisional excitation or cooling of ions, and evaporative cooling in cluster ions.

General polygon mesh discrete element method for arbitrarily shaped particles and complex structures based on an energy-conserving contact model

General polygon mesh discrete element method for arbitrarily shaped particles and complex structures based on an energy-conserving contact model

Dynamic evaluation of environmental-economic performance of vehicle emission reduction policy from the perspective of the loss-aversion effect

With increasing intensification of vehicle pollutants and CO2 emissions, it has become difficult to realize the co-control of pollution reduction and carbon reduction. Considering the limitations of the single-congestion charging policy, this study first analyzed the dual effect of charging on vehicle travel using the loss-aversion effect and constructed a decision algorithm of vehicle trips based on this effect. In the second step, the strategy of public publicity and public transport priority policy (PTPP) were introduced to establish a vehicle energy conservation and emission reduction (ECER) management model based on the mode of “charging + public publicity + public transport priority” (CPP). Finally, the following conclusions were drawn based on a dynamic simulation: (1) The single-charging mode can induce side effects, leading to a rebound in the number of vehicle trips. (2) Increasing the investment in publicity funds and expanding the scope of publicity forms can significantly raise the public's awareness of environmental protection and have a restraining effect on vehicle trips. (3) Compared with the single-charging policy, the CPP mode has multiple performance levels for the environment and economy. Moreover, the CO, CO2 emissions, and economic costs decreased by 45.67%, 31.93%, and 45%, respectively.

Phase Growth with Heat Diffusion in a Stochastic Lattice Model

When a stable phase is adjacent to a metastable phase with a planar interface, the stable phase grows. We propose a stochastic lattice model describing the phase growth accompanying heat diffusion. The model is based on an energy-conserving Potts model with a kinetic energy term defined on a two-dimensional lattice, where each site is sparse-randomly connected in one direction and local in the other direction. For this model, we calculate the stable and metastable phases exactly using statistical mechanics. Performing numerical simulations, we measure the displacement of the interface R(t). We observe the scaling relation \(R(t)=L_x \bar{\mathcal {R}} (Dt/L_x^2)\), where D is the thermal diffusion constant and \(L_x\) is the system size between the two heat baths. The scaling function \(\bar{\mathcal {R}}(z)\) shows \(\bar{\mathcal {R}}(z) \simeq z^{0.5}\) for \(z \ll z_c\) and \(\bar{\mathcal {R}}(z) \simeq z^{\alpha }\) for \(z \gg z_c\), where the cross-over value \(z_c\) and exponent \(\alpha \) depend on the temperatures of the baths, and \(0.5\le \alpha \le 1\). We then confirm that a deterministic phase-field model exhibits the same scaling relation. Moreover, numerical simulations of the phase-field model show that the cross-over value \(\bar{\mathcal {R}}(z_c)\) approaches zero when the stable phase becomes neutral.

An integrated model for energy conservation in IoT-enabled WSN using adaptive regional clustering and monkey inspired optimization

The advancement of the Internet of Things (IoT) technologies will play a significant role in the evolution of the smart city, smart healthcare, and smart grid applications. The key objective of IoT is to allow the autonomous exchange of valuable data between invisibly embedded devices with the help of some prominent technologies. Wireless Sensor Network (WSN) is one of the emerged technologies used for sensing and data exchange processes in IoT-based applications. Network sustainability and energy stability are the most significant multi-objectives to attain an energy-efficient IoT-based WSN (IWSN). Consequently, in order to handle these multi-objectives, a novel Adaptive Regional Clustering (ARC) scheme has been proposed in this paper by exploiting two appropriate methodologies. Primarily, location-based modelling is employed to gather the location information from each sensor node in the IWSN environment. Thereafter, an effective hierarchical clustering can be carried out with the assist of the ARC algorithm. The cluster head will be chosen based on node capacity and node trust value by implementing the Enhanced Monkey Inspired Optimization (EMIO) algorithm. Finally, the optimal cluster head node acts as an energy-efficient local director for conducting inter-cluster connectivity, data transmission, and other duties. The effectiveness of the proposed ARC-EMIO scheme has been assessed using the NS-3 simulator and the results evident that the proposed scheme guarantees better performance with an improved network lifetime of 35% and energy efficiency of 22% when compared with the existing state-of-the-art clustering techniques.

Analysis of Energy Conservation Big Data of Embedded Large Public Buildings and Construction of the Information Model by 5G

The problem of energy shortage has become one of the most serious problems in the process of economic development. The research is aimed at studying the energy conservation data and information model of large public buildings. Based on the theories of 5G technology, embedded system, and energy conservation of large public buildings, firstly, 5G technology is used to collect research data. Secondly, some large public buildings in Northwest China are analyzed for energy conservation by using ZigBee and other related technologies and algorithms. Finally, the office buildings in large public buildings are used as samples for the construction of the information model to be analyzed. The research results denote that large public buildings are mainly concentrated in hospitals, hotels, shopping malls, and so on. The south-facing window to wall ratio is higher than that of the north-facing window to wall ratio, and the east-west-facing window to wall ratio has the lowest probability of appearing. In addition, the thermal conductivity of the roof of most of the large buildings is less than 1.0 W, while the thermal conductivity of the outer wall of the roof is distributed around 2.5 W, and the thermal conductivity of the outer wall is around 0.6 W. Finally, commercial buildings have higher heating and cooling loads than residential buildings. In the construction of the information model for energy conservation of large public buildings, the neural networks (NNs) and clustering analysis algorithm are introduced into the prediction model of energy consumption data, and it is found that compared with the actual observed value, the overall trend shows consistency, both of which are periodic fluctuations. However, there are still some errors in some data. Therefore, an analysis of energy conservation data of embedded large public buildings and the construction of information models based on 5G has important guiding significance for the construction industry to improve business performance and market competitiveness.

Beyond Poiseuille flow: A transient energy-conserving model for flow through fractures of varying aperture

Large-scale models of fluid flow through fractures are almost exclusively based on Poiseuille flow (the cubic law). When the fracture aperture is time and/or spatially varying, flow is transient, and/or flow rates are modest (Re≥1), Poiseuille flow predictions can deviate substantially from the full Navier–Stokes solution and generally do not satisfy conservation of energy. A new Reduced Dimension Fracture Flow (RDFF) model is derived which more accurately predicts transient fracture flow for incompressible fluids with modest Reynolds numbers. The RDFF model is derived from the two-dimensional Navier–Stokes equations and yields a two-field model (fluid flux and pressure) governed by conservation of mass and momentum. The RDFF model conserves energy and is shown to include both Poiseuille flow and Forchheimer flow as limiting cases. The performance of the RDFF model is compared to the existing Poiseuille flow model and the solution to the full Navier–Stokes equations in three benchmarks problems. The RDFF model demonstrates complex transient and inertial behaviours not previously captured and produces up to 400% improvements in error over Poiseuille flow in steady-state flow conditions for 1≤Re≤100. The RDFF model is demonstrated to be superior in application where the Reynold’s number is modest and when aperture varies in space and/or time.