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At least 883 records · Page 49

Assessment of frequency and amplitude dependence on the cyclic degradation of polyurethane foams

Many energy absorption applications utilize flexible polymeric foams for their viscoelastic properties. It is desired that the material will perform consistently across repeated compression cycles. This study examines the effect of fatigue at low strain rates on the viscoelasticity of open-cell polyurethane foam. Six polyurethanes of the same base composition with two porosities (70% and 80%) and three chemical indexes (79i, 100i, and 121i) are tested. Large deformation cyclic compression of the foams is conducted on a universal testing system (UTS). These data are then post-processed leveraging dynamic mechanical analysis Fourier transform rheology to characterize changes in the viscoelasticity of the materials over fatigue cycles. Results show that foams can increase or decrease in stiffness up to 10% over 10 4 cycles. Specifically, higher chemical index, higher excitation frequency, and larger excitation amplitude correlate with a more pronounced decrease in stiffness. Damping can also change by 15% and correlates with chemical index and excitation frequency. Consequently, the findings suggest that internal foam structure and bulk material properties as well as applied loading parameters affect the viscoelastic fatigue response of flexible polymeric foams.

36 MATERIALS SCIENCE↗

Electron energy levels determining cathode electrolyte interphase formation

Cathode electrolyte interphase (CEI) has a significant impact on the performance of rechargeable batteries and is gaining increasing attention. Understanding the fundamental and detailed CEI formation mechanism is of critical importance for battery chemistry. Herein, a diverse of characterization tools are utilized to comprehensively analyze the composition of the CEI layer as well as its formation mechanism by LiCoO 2 (LCO) cathode. We reveal that CEI is mainly composed of the reduction products of electrolyte and it only parasitizes the degraded LCO surface which has transformed into a disordered spinel structure due to oxygen loss and lithium depletion. Based on the energy diagram and the chemical potential analysis, the CEI formation process has been well explained, and the proposed CEI formation mechanism is further experimentally validated. This work highlights that the CEI formation process is nearly identical to that of the anode-electrolyte-interphase, both of which are generated due to the electrolyte directly in contact with the low chemical potential electrode material. This work can deepen and refresh our understanding of CEI.

LiCoO2↗

Computational study of the effect of core–skin structure on the mechanical properties of carbon nanofibers

The effect of the core–skin structure on the mechanical properties of carbon nanofibers is investigated in large-scale molecular dynamics simulations of tensile deformation of carbon nanofibers with the core–skin and homogeneous structures. Contrary to an established notion of the deleterious effect of the skin layer on the strength of carbon fibers, the presence of a high-quality skin layer is found to increase both the Young’s modulus and tensile strength of the nanofiber. A detailed analysis of the fracture process indicates that the nanofiber strengthening is related to the ability of skin layer to suppress crack nucleation at the core–skin interface. Furthermore, the computational predictions suggest that the design of new approaches to carbon fiber manufacturing and processing leading to the generation of a high-quality skin layer while avoiding the introduction of structural defects at the core–skin interface may yield a significant enhancement of the mechanical properties of carbon fibers.

36 MATERIALS SCIENCE↗

Atikokan Digital Twin: Machine learning in a biomass energy system

The Atikokan Generating Station, operated by Ontario Power Generation, has a 200 MW, biomass-fired tower boiler that operates on a dispatch schedule with a five-minute cycle. The boiler is generally operated in the range of 40–100 MW using two of five burner levels. In order to optimize boiler performance, we propose the implementation of a unique digital twin. Our digital twin abstraction couples Bayesian inference from science-based models and from observations (machine learning) with decision theory to predict operating-variable set points that optimize the physical asset (the boiler) in the presence of uncertainty (artificial intelligence). We focus this paper on the continuous Bayesian machine learning part of the Atikokan Digital Twin; we discuss decision theory in a companion paper. We identify and learn about 12 operational, model, and measured-output parameters and their uncertainties from high-fidelity, science-based simulations of the Atikokan boiler and from the observed measurements at the power plant. Since the goal of the Atikokan Digital Twin is to implement it online in real time, we require fast function evaluations for the quantities of interest extracted from the simulations in the Bayesian analysis. We use Gaussian process regression/interpolation to create accurate, robust surrogate models. We define the Bayesian priors and likelihood function and solve for the posterior distributions of the 12 parameters. Here we then propagate these distributions (i.e., parameters with uncertainty) into the predicted distributions of 790 quantities of interest to learn about the relative importance of various sources of error including experimental, model, and operating-parameter errors.

09 BIOMASS FUELS↗

PyAlbany: A Python interface to the C++ multiphysics solver Albany

Albany is a parallel C++ finite element library for solving forward and inverse problems involving partial differential equations (PDEs). In this paper we introduce PyAlbany, a newly developed Python interface to the Albany library. PyAlbany can be used to effectively drive Albany enabling fast and easy analysis and post-processing of applications based on PDEs that are pre-implemented in Albany. PyAlbany relies on the library PyBind11 to bind Python with C++ Albany code. Here we detail the implementation of PyAlbany and showcase its capabilities through a number of examples targeting a heat-diffusion problem. In particular we consider the following: (1) the generation of samples for a Monte Carlo application, (2) a scalability study, (3) a study of parameters on the performance of a linear solver, and finally (4) a tool for performing eigenvalue decompositions of matrix-free operators for a Bayesian inference application.

97 MATHEMATICS AND COMPUTING↗

Chemically and mechanically recyclable polyester-based multilayer plastics

Approximately 100 million tons of multilayered plastics (MLPs) are produced each year worldwide but are not recycled due to their complex structure. Here, this work aims to design polyester-based multilayer plastics (80–100 % polyester) that provide barrier performance comparable to typical 9–12-layer commercial MLPs, while also enabling both chemical recycling (back to parent monomer) and mechanical recycling (grind-and-melt reprocessing). Such dual recyclability is not achievable with non-polyester multilayers, such as all-polyolefin systems. Furthermore, we emphasize how the multilayer architecture was tailored to balance barrier properties, mechanical integrity, and end-of-life recyclability for both flexible and rigid packaging applications. Two main categories of polyester-based MLPs are reported; in the first type, poly(butylene adipate-co-terephthalate) (PBAT)-70 % polyglycolic acid (PGA) is used as middle barrier layer, while in second type, middle barrier layer is Ethylene-vinyl alcohol (EVOH) copolymers. Polyethylene terephthalate (PET) was used as a structural layer, while either PBAT or poly(butylene succinate) (PBS) was used to enable thermal sealing and serve as the product contact layer. These MLPs are recycled by both chemical and mechanical recycling processes. Techno-economic analysis (TEA) shows that MLPs incorporating EVOH as barrier layer have similar or lower selling costs (0.32 $\$$/m 2 ) than commercial MLPs. Life cycle assessment (LCA) indicates EVOH-based MLPs have a lower carbon footprint and lower energy consumption relative to commercial MLP benchmarks. This work offers simplified MLPs that are easy to manufacture and ready to recycle, which will significantly reduce environmental impact of MLP packaging while also providing a cost-effective and practical solution for industry.

Barrier properties↗

A decision support tool for e-waste recycling operations using the hen-and-chicks bio-inspired optimization metaheuristic

E-waste from end-of-life electrical and electronic devices is one of the fastest growing waste streams from households and businesses. E-waste recycling yields environmental sustainability and economic benefits. Due to continuous changes in e-waste types and compositions, recycling businesses face challenges to optimize their operational configuration to achieve better economic and environmental performance. To help e-waste recyclers mitigate this problem, we have developed a modular decision support tool called the Comprehensive Manufacturing Assessment Tool (CMAT) that can simulate both e-waste recycling operations and economics. This tool can give valuable insights regarding the profitability of the entire operation and different e-waste types. In addition, a new bio-inspired metaheuristic optimization algorithm, hen-and-chicks optimization (HACO), was developed to assign manpower to different workstations to maximize operational efficiencies. According to the results of our case study, laptops, desktops, and computer peripherals are the three electronic waste products that produce the most profit. Our examination of the sensitivity of material prices shows that the price of steel has the most significant influence on total profit, because it is the most widely used material in the majority of electronic devices. We have released the decision support tool as open-source software under a general public license. It could be customized for other recycling industries beyond e-waste to achieve business sustainability by making their operations more efficient.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A practical approach for identifying various polarization behaviors of redox-stable electrodes in symmetrical solid oxide fuel cells

In symmetrical solid oxide fuel cells, comprehensively understanding the elementary reaction processes and the polarization behaviors of redox-stable electrode materials is critical for further optimization of the electrode performance. In this work, a systematical and practical approach, based on electrochemical impedance spectroscopy technology, is applied to identify the rate-limiting elementary reactions of the redox-stable electrodes. The feasibility of this proposed method is demonstrated in symmetrical solid oxide fuel cells with Sr 2 Fe 1.5 Mo 0.5 O 6-σ -Ce 0.9 Gd 0.1 O 1.95 as electrodes. Based on the characteristic frequency ranges and the experimental results tested under various fuel gas components, operating temperatures, and discharge current densities, the rate-limiting steps of the cathode are associated with the formation of adsorbed oxygen ions and the combination of oxygen ions and oxygen vacancies, while the rate-limiting steps of the anode are ascribed to the hydrogen dissociated adsorption and the steam desorption processes. This experimental and analysis framework can be straightforwardly extended to other electrode materials to unravel their electrochemical performance in detail.

25 ENERGY STORAGE↗

JTAG-based PLC memory acquisition framework for industrial control systems

In industrial control systems (ICS), programmable logic controllers (PLC) are the embedded devices that directly control and monitor critical industrial infrastructure processes such as nuclear plants and power grid stations. Cyberattacks often target PLCs to sabotage a physical process. A memory forensic analysis of a suspect PLC can answer questions about an attack, including compromised firmware and manipulation of PLC control logic code and I/O devices. Given physical access to a PLC, collecting forensic information from the PLC memory at the hardware-level is risky and challenging. It may cause the PLC to crash or hang since PLCs have proprietary, legacy hardware with heterogeneous architecture. This paper addresses this research problem and proposes a novel JTAG (Joint Test Action Group)-based framework, Kyros, for reliable PLC memory acquisition. Kyros systematically creates a JTAG profile of a PLC through hardware assessment, JTAG pins identification, memory map creation, and optimizing acquisition parameters. It also facilitates the community of interest (such as ICS owners, operators, and vendors) to develop the JTAG profiles of PLCs. Further, we present a case study of Kyros implementation over Allen-Bradley 1756-A10/B to help understand the framework's application on a real-world PLC used in industry settings. The sample PLC memory dumps are shared with the research community to facilitate further research.

Rais, Muhammad Haris↗

Tutorial: Langevin Dynamics methods for aerosol particle trajectory simulations and collision rate constant modeling

The Langevin Dynamics (LD) method (also known in the literature as Brownian Dynamics) is routinely used to simulate aerosol particle trajectories for transport rate constant calculations as well as to understand aerosol particle transport in internal and external fluid flows. This tutorial intends to explain the methodological details of setting up a LD simulation of a population of aerosol particles and to deduce rate constants from an ensemble of classical trajectories. We discuss the applicability and limitations of the translational Langevin equation to model the combined stochastic and deterministic motion of particles in fields of force or fluid flow. The drag force and stochastic “diffusion” force terms that appear in the Langevin equation are discussed elaborately, along with a summary of common forces relevant to aerosol systems (electrostatic, gravity, van der Waals, …); a commonly used first order and a fourth order Runge-Kutta time stepping schemes for linear stochastic ordinary differential equations are presented. A MATLAB® implementation of a LD code for simulating particle settling under gravity using the first order scheme is included for illustration. Scaling analysis of aerosol transport processes and the selection of timestep and domain size for trajectory simulations are demonstrated through two specific aerosol processes: particle diffusion charging and coagulation. Fortran® implementations of the first order and fourth order time-stepping schemes are included for simulating the 3D motion of a particle in a periodic domain. Lastly, potential applications and caveats to the usage of LD are included as a summary.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Porosity in Sr 1-x Ca x FeO 3-δ oxygen carriers: The role of surface area and pretreatment on storage activity

Perovskite oxides have generated interest as robust, low-temperature oxygen carrier materials for a variety of clean energy applications, including chemical looping gasification and air separations. Methods to improve O 2 desorption kinetics are vital to allow these carriers to compete economically with traditional metal oxide carriers or cryogenic separations. In this report we investigated the cumulative roles that surface area, pretreatment, and elemental composition have on the oxygen storage properties of a state-of-the-art carrier system, Sr 1-x Ca x FeO 3-δ (x = 0.20, 0.25, 0.30) synthesized using multiple methods. Porous materials synthesized by the Pechini, or citrate, method had their surface area controlled using the synthesis temperature. The high surface area of the Sr 0.7 Ca 0.3 FeO 3-δ materials is most beneficial at low operating temperatures, such as 350 and 400 °C, as their reduction rates are twice as fast as those obtained with their bulk counterparts. These effects are observed at higher operating temperatures and within a single composition, but temperature tunability using variable Ca 2+ substitution in the Sr 1-x Ca x FeO 3-δ overshadows the improvements gained from higher surface areas. Additionally, we establish that pretreatment in N2 at an elevated temperature is necessary to enhance kinetics further. For maximum efficiency, pretreatment at the synthesis temperature is suggested for the Pechini method-synthesized systems, whereas 800 °C is adequate for bulk materials.

36 MATERIALS SCIENCE↗

A conceptual model for how to design for building envelope characteristics. Impact of thermal comfort intervals and thermal mass on commercial buildings in U.S. climates

The paper presents a simplified conceptual model for energy demand calculations based on building envelope characteristics, thermal mass and local climate. It is based on a network model and lumped analysis of the dynamic process. Characteristic parameters for the buildings are suggested; Driving temperature (DT), Driving temperature difference, (DTD), External Load Temperature (ELT), and Thermal Load Resistance (TLR). The Building Envelope Performance ( BEP 0 ), based on a controlled constant indoor temperature is introduced. Solution techniques using stable explicit forward differences based on analytical solutions are derived. The conceptual model has been used for mapping the Driving temperature difference and introduced two performance factors and . The first factor represents the effect of thermal comfort interval and thermal mass on the energy demand. The latter represents the ratio between cooling and heating energy demand. These three parameters and factors have been visualized on U.S. maps and enable a possibility to communicate the demand of energy, and cooling and the coupling to building characteristics, in a concise way.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Laser strengthening of additive manufactured edge seal for vacuum insulated glazing with micro-size glass frit

Sealing of glass edge is a key step in developing cost-effective and durable vacuum insulated glazing for the drive towards net-zero energy buildings. In this study, to achieve a high-strength sealing with scalable and low-cost processing, we investigated a novel sealing method based on additive manufacturing and laser process and reported quantitative analysis of the laser assisted method sealing strength and the requirement of vacuum insulation glazing. Micro-size glass frits in printing ink and a continuous-wave laser curing were employed to allow the formation of a hermetic bonding layer with low thermal budget. Controlling various sealing parameters including laser traveling speed, spot diameter, and laser power, the water seepage and mechanical strength of the resulting glass-to-glass bonding were examined. Through the response surface methodology, we identified the optimized sealing condition where the bonding strength reached 5.68 MPa. A comparation of the bonding strength between thermal sealing method and laser-assisted method has been analyzed as well.

42 ENGINEERING↗

Analysis of contact conditions and microstructure evolution in shear assisted processing and extrusion using smoothed particle hydrodynamics method

Shear assisted processing and extrusion (ShAPE) is a solid-phase processing technique that adds an additional shear force as compared with a conventional extrusion approach. Recently, ShAPE has demonstrated the capability of extruding high-performance aluminum alloy 7075 (AA7075) tubes at speeds up to 12.2 m/min without surface tearing. However, the relationship among the ShAPE processing parameters, thermomechanical conditions, contact conditions, heat generation, and microstructure evolution remains primarily empirical because an insightful understanding of the associated physics is still lacking. To help elucidate these relationships, this work proposes a thermomechanical meshfree model for the first time for ShAPE processing of AA7075 using the smoothed particle hydrodynamics (SPH) method. The meshfree model is first validated thoroughly by experimental data in terms of material flow, die face temperature, and extrusion force with various processing parameters. The validated model is then used to analyze the steady-state contact conditions and heat generation rates during ShAPE processing. Distributions of the average grain size of AA7075 being extruded are calculated using the SPH model output. The meshfree model results reveal that extrusions conducted at lower temperatures and higher strain rates yield more refined grains and possibly higher material strength, which is also consistent with the experimental observations.

36 MATERIALS SCIENCE↗

Stable electrospray signal on a microfabricated glass chip with three-dimensional open edge and tiered depth geometries

This paper presents the microfabrication and performance of a three-dimensional electrospray ionization (ESI) emitter tip made from glass, which achieves stable current signals important for chemical analysis. Our novel microfabrication process and custom-built signal conditioning hardware provides the advantage of providing accurate features and steady signals. The fabrication process relies on standard microfabrication techniques (i.e., deposition, photolithography, and wet etching). This fabrication method involves the novel application of two layers of positive and negative photoresists in addition to Parafilm® wax tape. Open edge and tiered depth details were successfully created from a multilayer planar mask. This is a benefit for integrated miniaturized and microfluidic systems that often require micro features for their functionality but relatively large millimeter size features for their physical periphery. We demonstrate the fundamental performance of electrospray with this microfluidic chip. The emitter tip was fixed on a linear axis stage with high resolution (10 μm) to finely control the tip distance from a metal counter electrode plate. Further, a custom printed circuit board system was built to safely control four voltages applied to the microchip ports from a single high voltage power supply. To readily form the electrospray, non-aqueous solvents were used for their low viscosity and a constant voltage of +2.7 kV was applied to the sheath electrospray microchannel. The liquid being sprayed was 80/20 (v/v) methanol/acetonitrile with 0.1% acetic acid in the sheath microchannel and with ammonium acetate (10–40 mM) in its remaining microchannels. The electrospray signal was measured in response to varying the distance (1.4 to 1.6mm) between the electrospray emitter tip and a metal counter electrode plate in addition to the varying concentration of the background electrolyte, ammonium acetate. Stable and repeatable electrospray signal showed linear relationships with emitter tip distance and concentration (r 2 ≥ 0.95).

42 ENGINEERING↗

Additive manufacturing of soft and hard magnetic materials used in electrical machines

Soft and hard magnetic materials were fabricated using additive manufacturing (AM) for use in 3D electrical machines. The effect of the characteristics and the nature of the magnetic feedstock powders was evaluated for both the cold spray (CS) and the fused filament fabrication (FFF) processes. 3D finite element analysis (FEA) was used to develop new motor topologies based on the advantages offered by AM. FEA optimization also allowed the identification of the most critical material properties and is thus a powerful tool to facilitate material development.

Bernier, Fabrice↗