Effects Of Additional Parameters Research Articles

Design–operation gap caused by parameter variance in HVAC system control sequences: A simulation-based study on energy efficiency and temperature controllability

During the design phase, the annual energy consumption of heating, ventilation, and air-conditioning (HVAC) systems is frequently simplified or fixed under certain assumptions due to uncertain parameters within the control sequence, resulting in a performance gap between the intended and actual performances. This study assessed the impact of six uncertain parameters on system energy consumption and indoor temperature control under various updating scenarios. First, sensitivity analysis was conducted using the one-at-a-time method to identify the influential impact of the single uncertain parameter. Then, mutual impact analysis was conducted to showcase how different parameters affect each other, and mixed impact analysis was applied to evaluate how intended design performance converges to actual operating outcomes. A detailed physical model of a single-zone variable air volume system was developed to enable a comprehensive evaluation across different operational conditions. The results indicate that a 10% change in some parameters can lead to a 20∼30% increase in energy consumption, especially during low-load winter months. Properly evaluating the influence of one parameter is difficult without taking the effects of additional parameters into account, and some combinations of parameters can significantly decrease the system performance. These results underscore the necessity of considering the updating and combination scenarios of different parameters within the control sequences during the design phase.

A Comprehensive Study on the Styrene–GTR Radical Graft Polymerization: Combination of an Experimental Approach, on Different Scales, with Machine Learning Modeling

The study of the styrene–Ground Tire Rubber (GTR) graft radical polymerization is particularly challenging due to the complexity of the underlying kinetic mechanisms and nature of GTR. In this work, an experimental study on two scales (∼10 mL and ∼100 mL) and a machine learning (ML) modeling approach are combined to establish a quantitative relationship between operating conditions and styrene conversion. The two-scale experimental approach enables to verify the impact of upscaling on thermal and mixing effects that are particularly important in this heterogeneous system, as also evidenced in previous works. The adopted experimental setups are designed in view of multiple data production, while paying specific attention in data reliability by eliminating the uncertainty related to sampling for analyses. At the same time, all the potential sources of uncertainty, such as the mass loss along the different steps of the process and the precision of the experimental equipment, are also carefully identified and monitored. The experimental results on both scales validate previously observed effects of GTR, benzoyl peroxide initiator and temperature on styrene conversion but, at the same time, reveal the need of an efficient design of the experimental procedure in terms of mixing and of monitoring uncertainties. Subsequently, the most reliable experimental data (i.e., 69 data from the 10 mL system) are used for the screening of a series of diverse supervised-learning regression ML models and the optimization of the hyperparameters of the best-performing ones. These are gradient boosting, multilayer perceptrons and random forest with, respectively, a test R2 of 0.91 ± 0.04, 0.90 ± 0.04 and 0.89 ± 0.05. Finally, the effect of additional parameters, such as the scaling method, the number of folds and the random partitioning of data in the train/test splits, as well as the integration of the experimental uncertainties in the learning procedure, are exploited as means to improve the performance of the developed models.

(Invited) Battphase – a Convergent, Non-Oscillatory, Efficient Algorithm and Code for Predicting Shape Changes in Lithium Metal Batteries Using Phase-Field Models

Electrochemical models at different scales and varying levels of complexity have been used in the literature to study the evolution of the anode surface in lithium metal batteries. This includes continuum, mesoscale (phase-field approaches), and multiscale models.1-5 Thermodynamics-based equations have been used to study phase changes in lithium batteries using phase-field approaches. However, grid convergence studies and the effect of additional parameters needed to simulate these models are not well-documented in the literature. In this talk, using a motivating example of a moving boundary model in one- and two-dimensions, we show how one can properly formulate phase-field models using the immersed interface/domain approach, implement robust and efficient algorithms for the same and analyze the results (Figure 1). An open-access code with no restrictions is provided as well. The talk concludes with some thoughts on the computational efficiency of phase-field models for simulating dendritic growth. Acknowledgements The authors would like to express gratitude to Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Vehicle Technologies of the DOE through the Advanced Battery Material Research (BMR) Program (Battery500 consortium). This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government. Supported by the Laboratory Directed Research and Development program at Sandia National Laboratories, a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525. VS acknowledges interactions with Dr. Srikanth Vedantam from IIT Madras, India and Dr. Daniel Wheeler from National Institute of Standards and Technology for early discussions on phase-field and level-set methods. VS also acknowledges Richard Braatz from Massachusetts Institute of Technology for pointing out the poor results from standard algorithms because of the convective nature of the models.

BattPhase—A Convergent, Non-Oscillatory, Efficient Algorithm and Code for Predicting Shape Changes in Lithium Metal Batteries Using Phase-Field Models: Part I. Secondary Current Distribution

Electrochemical models at different scales and varying levels of complexity have been used in the literature to study the evolution of the anode surface in lithium metal batteries. This includes continuum, mesoscale (phase-field approaches), and multiscale models. Thermodynamics-based equations have been used to study phase changes in lithium batteries using phase-field approaches. However, grid convergence studies and the effect of additional parameters needed to simulate these models are not well-documented in the literature. In this paper, using a motivating example of a moving boundary model in one- and two-dimensions, we show how one can formulate phase-field models, implement algorithms for the same and analyze the results. An open-access code with no restrictions is provided as well. The article concludes with some thoughts on the computational efficiency of phase-field models for simulating dendritic growth.

A review on parameters affecting nanoparticles stabilized foam performance based on recent analyses

In recent years, much attention has been paid to the addition of nanoparticles (NPs) into the surfactant foam structure to form durable foams. Although surfactant foam as an enhanced oil recovery (EOR) technique significantly increases the viscosity of the injected fluid compared to gas injection, it has been observed that the foam structure does not have the required stability in cases such as high temperatures and high salinity. Although NP addition increases stability, the extent of this increase depends on several parameters, including NP properties (i.e., size, type, surface wettability) and reservoir properties (i.e., salinity of formation water, presence of oil, reservoir temperature), process parameters (i.e., NP concentration and flow rate), synergistic effects between the surface charge of NPs and the net charge of surfactant, and NP loss in the porous medium. This study aims to review and summarize the findings of previous studies to conclude the effects of each of the parameters above on foam stability, identify differences, and determine gaps for future studies. Throughout this report, a study background is provided, followed by the concept of stability and how to determine it in different tests for NP-surfactant foam. Next, the mechanisms of increasing stability by NP addition are briefly presented. Lastly, previous findings related to the effect of each parameter on NP foam stability are presented and discussed. Although several detailed reviews of NP-stabilized foam have been published previously, the present study differs from them in that the effects of additional parameters were investigated by reviewing new findings. Moreover, an attempt has been made to discuss the effects of parameters from different angles and according to their role in the mechanisms of NP-stabilized foam, such as particle detachment energy and maximum capillary pressure. The findings of this review show that i) oil presence lowers foam stability, ii) increasing NP concentration as well as decreasing NP size, temperature, NP retention, and salinity lead to increased stability, and iii) for parameters including NP surface wettability, NP types, and shear rate/flow velocity there are optimum points that result in the best foam performance. NP loss in a porous medium is an economically damaging process that occurs through mechanisms including adsorption, mechanical entrapment and log-jamming, and particles settling due to gravity. Depending on the type of mechanism, the strategy for minimizing or removing the influence of these mechanisms differs. However, there is currently no way to determine and measure the contribution of each of these mechanisms to the total retention in dynamic tests, which could be a specific topic for future research.

Highly sensitive label-free bio-interfacial colorimetric sensor based on silk fibroin-gold nanocomposite for facile detection of chlorpyrifos pesticide

Herein, the preparation of gold nanoparticles-silk fibroin (SF-AuNPs) dispersion and its label-free colorimetric detection of the organophosphate pesticide, namely chlorpyrifos, at ppb level are reported. The silk fibroin solution was extracted from B. mori silk after performing degumming, dissolving and dialysis steps. This fibroin solution was used for synthesis of gold nanoparticles in-situ without using any external reducing and capping agent. X-ray Diffractometry (XRD), Field Emission Transmission Electron Microscopy (FETEM) along with Surface Plasmon Resonance based optical evaluation confirmed generation of gold nanoparticles within SF matrix. The resultant SF-AuNPs dispersion exhibited rapid and excellent colorimetric pesticide sensing response even at 10 ppb concentration. Effect of additional parameters viz. pH, ionic concentration and interference from other pesticide samples was also studied. Notably, SF-AuNPs dispersion exhibited selective colorimetric pesticide sensing response which can be calibrated. Furthermore, this method was extended to various simulated real life samples such as tap water, soil and agricultural products including plant residues to successfully detect the presence of chlorpyrifos pesticide. The proposed colorimetric sensor system is facile yet effective and can be employed by novice rural population and expert researchers alike. It can be exploited as preliminary tool for label-free colorimetric chlorpyrifos pesticide sensing in water and agricultural products.

Multi-mode heat transfer analysis during freezing of an encapsulated storage medium

Simultaneous conduction, convection and thermal radiation have been analyzed during the freezing of a non-opaque, non-gray phase change material (PCM) encapsulated in a closed spherical container and heated at relatively high temperatures (250⩽T⩽325°C). In contrast to the well-known conduction-dominated model of the single phase Stefan problem, in the present study the influence of the participating thermal radiation and the buoyancy induced natural convection within the melt layer is highlighted and analyzed. A two-dimensional, axisymmetric, transient model has been solved numerically. The discrete ordinate method was used to solve the equation of radiative transfer and the finite volume scheme was used to solve the equations for mass, momentum and energy conservation. The effect of additional parameters like the shell size and the external heat transfer coefficient imposed on the outer shell surface as a boundary condition have also been analyzed. It was found that the contribution of thermal radiation on the solidification process of NaNO3 is to reduce the solidification time by 17% as compared with the limiting case where thermal radiation is neglected.

Torsional analysis of heterogeneous magnetic circular cylinder

In this paper, the exact closed-form solutions for torsional analysis of heterogeneous magnetostrictive circular cylinder are derived. The cylinder is subjected to the action of a magnetic field produced by a constant longitudinal current density. It is also acted upon by a particular kind of shearing stress at its upper base. The rigidity of the cylinder is graded through its axial direction from one material at the lower base to another material at the upper base. The distributions of circumferential displacement and shear stresses are presented through the radial and axial directions of the cylinder. The influence of the magnetostrictive parameter is discussed. The effects of additional parameters are investigated.

Spline regression models for complex multi-modal regulatory networks

Complex regulatory networks often have to be further expanded and improved with regard to the unknown effects of additional parameters and factors that can emit a disturbing influence on the key variables under consideration. The concept of target-environment (TE) networks provides a holistic framework for the analysis of such parameter-dependent multi-modal systems. In this study, we consider time-discrete TE regulatory systems with spline entries. We introduce a new regression model for these particular two-modal systems that allows us to determine the unknown system parameters by applying the multivariate adaptive regression spline (MARS) technique and the newly developed conic multivariate adaptive regression spline (CMARS) method. We obtain a relaxation by means of continuous optimization, especially, conic quadratic programming (CQP) that could be conducted by interior point methods. Finally, a numerical example demonstrates the efficiency of the spline-based approach.

An interactive numerical model of diode-pumped, Q-switched/cavity-dumped lasers

We have developed an interactive numerical model, which describes the operational characteristics of multiple diode-pumped laser systems that are Q-switched or Q-switched/cavity-dumped. These are the first computer-generated results obtained using rate equations that incorporate the 'inversion reduction parameter' gamma . The quantity gamma can partially take into account effects of relaxation and thermally driven transfer, which occurs between laser level multiplets. A value of gamma near unity is found for the Nd:YAG lasers, implying considerable thermal relaxation of the lower lasing level, and it may also imply some thermal refreshing of the upper lasing level. A value of gamma =2 is found to fit the Ti:sapphire results, indicating that the lower lasing level is not relaxed during laser pulse development. The interactive nature of the model allows for variation of all the significant parameters required to generate a Q-switched or cavity-dumped pulse. Input information is expressed in terms of standard variables such as stored energy, optical and dissipative losses and stimulated emission and pump absorption cross sections. The effects of additional parameters, including the Gaussian beam profile of the cavity, the induced losses associated with the rise and fall times of the Q-switch and cavity-dump Pockels cell, and the induced thermal lensing effects produced by the pump rate in the gain medium are taken into account. The width and energy of the cavity-dumped laser pulse can also be studied in the model by varying the cavity-dump voltage switch transition time.