Chemical Methods for Hydrolyzing Dairy Manure Fiber: A Concise Review

This paper reviews the chemical hydrolysis processes of dairy manure fiber to make its sugar accessible to microorganisms during anaerobic digestion and identifies obstacles and opportunities. Researchers, so far, investigated acid, alkali, sulfite, and advanced oxidation processes (such as hydrogen peroxide assisted by microwave/ultrasound irradiation, conventional boiling, and wet oxidation), or their combinations. Generally, dilute acid (3–10%) is less effective than concentrated acid (12.5–75%), which decrystallizes the cellulose. Excessive alkaline may produce difficult-to-degrade oxycellulose. Therefore, multi-step acid hydrolysis (without alkaline) is preferred. Such processes yielded 84% and 80% manure-to-glucose and -xylose conversion, respectively. Acid pretreatment increases lignin concentration in the treated manure and hinders subsequent enzymatic processes but is compatible with fungal cellulolytic enzymes which favor low pH. Manure high alkalinity affects dilute acid pretreatment and lowers glucose yield. Accordingly, the ratio of manure to the chemical agent and its initial concentration, reaction temperature and duration, and manure fineness need optimization because they affect the hydrolysis rate. Optimizing these factors or combining processes should balance removing hemicellulose and/or lignin and increasing cellulose concentrations while not hindering any subsequent process. The reviewed methods are neither economical nor integratable with the on-farm anaerobic digestion. Economic analysis and energy balance should be monolithic components of the research. More research is required to assess the effects of nitrogen content on these processes, optimize it, and determine if another pretreatment is necessary.

A Data-Driven Method for Predicting Deformation of Machined Parts Using Sparse Monitored Deformation Data

In the aircraft industry, where high precision geometric control is vital, unexpected component deformation, due to the release of internal residual stress, can limit geometric accuracy and presents process control challenges. Prediction of component deformation is necessary so that corrective control strategy can be defined. However, existing prediction methods, that are mainly based on the prediction or measurement of residual stress, are limited and accurate deformation prediction is still a research challenge. To address this issue, this paper presents a data-driven method for deformation prediction based on the use of in-process monitored deformation data. Deformation, which is caused by an unbalanced internal residual stress field, can be accurately monitored during the machining process via an instrumented fixture device. The state of the internal stress field within the part is first estimated by the using the part deformation data collected during machining process, and then, the deformation caused by a subsequent machining process is predicted. Deep learning is used to establish the estimating module and predicting module. The estimating module is used to infer the unobservable residual stress field as vectors by using sparse deformation data. The inferred vector is then used to predict the deformation in the predicting module. The proposed method provides an effective way to predict deformation during the machining of monolithic components, which is demonstrated experimentally.

Wireless Power Transfer for 6G Network Using Monolithic Components on GaN

A novel architecture for Wireless Power Transfer (WPT) module usingmonolithic components on GaN is presented in this paper. The design ofsuch a WPT module receives DC power from solar panels, consists ofphotonic power converter (PPC), beamforming antenna, low pass filter,input matching network, rectifier, output matching network and logic circuit(off-chip) which are all integrated on a GaN chip. Our WPT componentsshow excellent simulated performance, for example, our novel beamforming antenna and multiple port wideband antenna have a gain of 8.7 dBand 7.3 dB respectively. We have added a band pass filter to the rectifieroutput which gives two benefits to the circuit. The first one is filteringcircuit will remove unwanted harmonics before collecting DC power andsecond is filter will boost the efficiency of rectifier by optimizing the loadimpedance. Our proposed rectifier has RF-DC conversion efficiency of74% and 67% with beam-forming antenna and multiple port wide bandantenna respectively. Our WPT module is designed to charge a rechargeablebattery (3 V and 1 mA) of a radio module which will be used between twoantennas in future 5G networks. We believe our proposed WPT modulearchitecture is unique and it is applicable to both microwave and millimeterwave systems such as 6G.

Machining Deformation Analysis of Aircraft Monolithic Components based on the Energy Method

In the process of machining aircraft monolithic components, the initial stress in the blank will cause machining deformation. Based on the energy method, an analytical mathematical model of machining deformation is presented in this paper. The key point is to transform the energy in the removed material into the deformation energy of the part after machining. The initial residual stress of 7050-T7451 aluminum alloy blank and single frame part are used as investigated case in the analytical model. For layer by layer machining, the deformation evolution is closely related to the tensile or compressive properties of the initial stress of removed material. Combined with the change of neutral axis position, The machining deformation is calculated by theoretical model. Then, FEM simulation is carried out to analyze the influence of stiffening ribs on machining deformation utilizing the semi-analytical model of equivalent bending stiffness. Furthermore, experiments are set up to verify the validity of the theory and FEM data. The results indicate that the deformation results of the experiment are consistent with that of theory and FEM model. Deformation is determined by energy of removed material. This paper provides a novel theoretical approaches for the further investigation of this issue.

Machining Deformation Analysis of Aircraft Monolithic Components Based on the Energy Method

In the process of machining aircraft monolithic components, the initial stress in the blank will cause machining deformation. Based on the energy method, an analytical mathematical model of machining deformation is presented in this paper. The key point is to transform the energy in the removed material into the deformation energy of the part after machining. The initial residual stress of 7050-T7451 aluminum alloy blank and single frame part are used as investigated case in the analytical model. For layer by layer machining, the deformation evolution is closely related to the tensile or compressive properties of the initial stress of removed material. Combined with the change of neutral axis position, The machining deformation is calculated by theoretical model. Then, FEM simulation is carried out to analyze the influence of stiffening ribs on machining deformation utilizing the semi-analytical model of equivalent bending stiffness. Furthermore, experiments are set up to verify the validity of the theory and FEM data. The results indicate that the deformation results of the experiment are consistent with that of theory and FEM model. Deformation is determined by energy of removed material. This paper provides a novel theoretical approaches for the further investigation of this issue.

Investigations on the surface quality of grinded inner contours using different manufacturing strategies on fused silica

In the field of optical manufacturing, fused silica has a high and constantly growing application potential. Its material advantages, such as low thermal expansion and high thermal shock resistance, as well as its high transparency from the ultraviolet to the infrared spectral range, result in a large number of application fields. For example, manufacturing processes in semiconductor technology require high-quality quartz materials throughout the wafer handling process to avoid non-permissible contamination and to withstand the high process temperatures. Another example are monolithic components for fiber preform manufacturing, where internal contours with high aspect ratios (e.g. component length to component diameter) and high surface qualities are required to draw fiber types with special properties. The demands on the complexity and accuracy of these components are constantly increasing, which is accompanied by the need to analyse and optimize modern CNC manufacturing techniques more and more. In the following, investigations on the grinding of internal contours with a high aspect ratio are presented, in which the influence of an ultrasonic assistance as well as different machining strategies are considered.

Process Parameters Optimization of Thin-Wall Machining for Wire Arc Additive Manufactured Parts

Additive manufacturing (AM) is an arising production process due to the possibility to produce monolithic components with complex shapes with one single process and without the need for special tooling. AM-produced parts still often require a machining phase, since their surface finish is not compliant with the strict requirements of the most advanced markets, such as aerospace, energy, and defense. Since reduced weight is a key requirement for these parts, they feature thin walls and webs, usually characterized by low stiffness, requiring the usage of low productivity machining parameters. The idea of this paper is to set up an approach which is able to predict the dynamics of a thin-walled part produced using AM. The knowledge of the workpiece dynamics evolution throughout the machining process can be used to carry out cutting parameter optimization with different objectives (e.g., chatter avoidance, force vibrations reduction). The developed approach exploits finite element (FE) analysis to predict the workpiece dynamics during the machining process, updating its changing geometry. The developed solution can automatically optimize the toolpath for the machining operation, generated by any Computer Aided Manufacturing (CAM) software updating spindle speed in accordance with the selected optimization strategies. The developed approach was tested using as a test case an airfoil.