Uncovering Microbiome Adaptations in a Full-Scale Biogas Plant: Insights from MAG-Centric Metagenomics and Metaproteomics.

The current focus on renewable energy in global policy highlights the importance of methane production from biomass through anaerobic digestion (AD). To improve biomass digestion while ensuring overall process stability, microbiome-based management strategies become more important. In this study, metagenomes and metaproteomes were used for metagenomically assembled genome (MAG)-centric analyses to investigate a full-scale biogas plant consisting of three differentially operated digesters. Microbial communities were analyzed regarding their taxonomic composition, functional potential, as well as functions expressed on the proteome level. Different abundances of genes and enzymes related to the biogas process could be mostly attributed to different process parameters. Individual MAGs exhibiting different abundances in the digesters were studied in detail, and their roles in the hydrolysis, acidogenesis and acetogenesis steps of anaerobic digestion could be assigned. Methanoculleus thermohydrogenotrophicum was an active hydrogenotrophic methanogen in all three digesters, whereas Methanothermobacter wolfeii was more prevalent at higher process temperatures. Further analysis focused on MAGs, which were abundant in all digesters, indicating their potential to ensure biogas process stability. The most prevalent MAG belonged to the class Limnochordia; this MAG was ubiquitous in all three digesters and exhibited activity in numerous pathways related to different steps of AD.

Additive manufacturing of multi-material parts - Design guidelines for manufacturing of 316L/CuCrZr in laser powder bed fusion.

Additive manufacturing (AM) can be used to produce multi-material parts in which the material can be varied voxel-wise in all three spatial directions. This means that the paradigm of the homogeneous material can be abandoned and local effects such as heat conduction or damping can be selectively adjusted in the part. Recently, continuous development of machine technology has allowed the production of multi-metal materials in laser powder bed fusion (PBF-LB/MM). Compared to other additive manufacturing processes for multi-material production, this allows greater design freedom and detail accuracy to be realized. However, due to the novel character of multi-material manufacturing in PBF-LB, the process knowledge for successful and reproducible fabrication is currently lacking. This paper focuses on establishing design guidelines for manufacturing the material pairing of stainless steel 316L (1.4404) and copper alloy CuCrZr (CW106C). The article is accompanied by the development of a specific process chain. As a result of this work, design guidelines for multi-material parts are available for the first time, in regard to arrangement, size, overhangs, economy, powder quality and laser scanning.

Analysis of potential materials for local production of a rail car component using additive manufacturing.

In the rail industry, unavailability of spare parts can have negative implications such as downtime and financial losses. Long lead times can be experienced in the process of replacing a damaged spare part. Some of the parts are expensive to produce in-house using conventional methods because of the tooling costs. It can be time consuming to wait for suppliers to replace the part if it is not produced locally. Proper maintenance of vehicles requires spare parts to be available timeously. It is necessary to investigate how parts can be produced using locally available technologies and materials. The aim of this study is to analyse potential materials that can be used to produce a rail car component. The use of Additive Manufacturing (AM) to produce parts on demand is a quicker and flexible approach when compared to conventional manufacturing methods. Taking advantage of the flexibility offered by the AM, three alternative high performance materials are considered to reduce the weight, improve functional performance and service life of the part. The performance of all the three materials are tested and analysed using Finite Element Analysis. The results of this study are useful in providing guidance on the development of a suitable process chain for producing the part locally. This demonstrates the capability of AM as a suitable approach for enabling local sustainable production of spare parts for the rail industry.

Influence of Process Parameters on Grain Size and Texture Evolution of Fe-3.2 wt.-% Si Non-Oriented Electrical Steels.

The magnetic properties of non-oriented electrical steel, widely used in electric machines, are closely related to the grain size and texture of the material. How to control the evolution of grain size and texture through processing in order to improve the magnetic properties is the research focus of this article. Therefore, the complete process chain of a non-oriented electrical steel with 3.2 wt.-% Si was studied with regard to hot rolling, cold rolling, and final annealing on laboratory scale. Through a comprehensive analysis of the process chain, the influence of important process parameters on the grain size and texture evolution as well as the magnetic properties was determined. It was found that furnace cooling after the last hot rolling pass led to a fully recrystallized grain structure with the favorable ND-rotated-cube component, and a large portion of this component was retained in the thin strip after cold rolling, resulting in a texture with a low γ-fiber and a high ND-cube component after final annealing at moderate to high temperatures. These promising results on a laboratory scale can be regarded as an effective way to control the processing on an industrial scale, to finally tailor the magnetic properties of non-oriented electrical steel according to their final application.

Integrated Process Simulation of Non-Oriented Electrical Steel.

A tailor-made microstructure, especially regarding grain size and texture, improves the magnetic properties of non-oriented electrical steels. One way to adjust the microstructure is to control the production and processing in great detail. Simulation and modeling approaches can help to evaluate the impact of different process parameters and finally select them appropriately. We present individual model approaches for hot rolling, cold rolling, annealing and shear cutting and aim to connect the models to account for the complex interrelationships between the process steps. A layer model combined with a microstructure model describes the grain size evolution during hot rolling. The crystal plasticity finite-element method (CPFEM) predicts the cold-rolling texture. Grain size and texture evolution during annealing is captured by the level-set method and the heat treatment model GraGLeS2D+. The impact of different grain sizes across the sheet thickness on residual stress state is evaluated by the surface model. All models take heterogeneous microstructures across the sheet thickness into account. Furthermore, a relationship is established between process and material parameters and magnetic properties. The basic mathematical principles of the models are explained and demonstrated using laboratory experiments on a non-oriented electrical steel with 3.16 wt.% Si as an example.

Influence of Subsequently Applied Mechanical and Thermal Loads on Surfaces Ground with Mechanical Main Impact.

To generate advanced properties for the wear resistance and fatigue life of components and allow for an improved, application-oriented development of part specifications, a precisely tailored initial machining or manufacturing process is necessary. In addition, it is important to know how subsequent machining steps or operational loads affect the components' condition. Residual stresses are a meaningful measurand for evaluating the modifications that a machining process induces into the material. The desired modifications should be specified regarding the final state for the required operational behavior. Thus, the stability of the modifications can be considered so that they can be beneficial in service. This investigation is part of fundamental research in the field of the Collaborative Research Center (CRC) "Process Signatures". By applying defined selected loads, the effects on machined surface layers are investigated since machined components are exposed to further loads during use. For this reason, experimental process chains are applied in this work to grind-strengthened specimens as possible application cases and corresponding loads. These experimental process chains consist of defined mechanical and thermal loads, which are applied to the specimens using a thermal and mechanical testing system. Furthermore, it is investigated how these additional loads affect the modifications previously introduced by the grinding process. The influence of the additional loads is evaluated by using radiographic and electron microscopic examinations. It can be observed that the sequence, as well as the type of the applied loads, play a significant role in the development of the modifications.

Laser Remelting Process Simulation and Optimization for Additive Manufacturing of Nickel-Based Super Alloys.

Nickel-based super alloys are popular for applications in the energy and aerospace industries due to their excellent corrosion and high-temperature resistance. Direct metal deposition (DMD) of nickel alloys has reached technology readiness for several applications, especially for the repair of turbomachinery components. However, issues related to part quality and defect formation during the DMD process still persist. Laser remelting can effectively prevent and repair defects during metal additive manufacturing (AM); however, very few studies have focused on numerical modeling and experimental process parameter optimization in this context. Therefore, the aim of this study is to investigate the effect of determining the remelting process parameters via numerical simulation and experimental analyses in order to optimize an industrial process chain for part repair by DMD. A heat conduction model analyzed 360 different process conditions, and the predicted melt geometry was compared with observations from a fluid flow model and experimental single tracks for selected reference conditions. Subsequently, the remelting process was applied to a demonstrator repair case. The results show that the models can well predict the melt pool shape and that the optimized remelting process increases the bonding quality between base and DMD materials. Therefore, DMD part fabrication and repair processes can benefit from the remelting step developed here.

Selective Laser Melting of Patient Individualized Osteosynthesis Plates-Digital to Physical Process Chain.

We report on the exemplified realization of a digital to physical process chain for a patient individualized osteosynthesis plate for the tarsal bone area. Anonymized patient-specific data of the right feet were captured by computer tomography, which were then digitally processed to generate a surface file format (standard tessellation language, STL) ready for additive manufacturing. Physical realization by selective laser melting in titanium using optimized parameter settings and post-processing by stress relief annealing results in a customized osteosynthesis plate with superior properties fulfilling medical demands. High fitting accuracy was demonstrated by applying the osteosynthesis plate to an equally good 3D printed bone model, which likewise was generated using the patient-specific computer tomography (CT) data employing selective laser sintering and polyamid 12. Proper fixation has been achieved without any further manipulation of the plate using standard screws, proving that based on CT data, individualized implants well adapted to the anatomical conditions can be accomplished without the need for additional steps, such as bending, cutting and shape trimming of precast bone plates during the surgical intervention. Beyond parameter optimization for selective laser melting, this exemplified digital to physical process chain highlights the potential of additive manufacturing for individualized osteosynthesis.

IT-Assisted Process Management in Healthcare.

Clinical processes need to be well understood before a new health IT tool can be introduced. Observations, interviews, surveys, or documentation analysis are carried out to systematically collect information to better understand a clinical process. To aggregate and visualize the collected information about a clinical process, use case diagrams can build a basis. Formal process models such as process chain diagrams or BPMN diagrams are well suited to model the process in detail. The objective of this chapter is to discuss these methods for analyzing and modeling clinical processes, as this is an important precondition for systematic process management in health care.

Evaluation of the energetic and environmental potential of the hydrothermal carbonization of biowaste: Modeling of the entire process chain.

This study outlines the entire process chain related to an industrial-sized hydrothermal carbonization (HTC) plant, which treats the organic fraction of municipal solid waste. A parameter study, carried out in laboratory-scaled experiments, was used to create a model starting with the substrate preparation and ending with the production of electricity. It was designed to be infinitely variable with respect to different reaction intensities within certain boundary conditions. Contrary to previous research endeavors, all components related to the HTC process and modules for the post-treatment of co-products including heat recovery and process water treatment were integrated. Based on this model, the claim that HTC-char is a more environmentally friendly energy carrier than lignite was investigated. In the realm of a life cycle assessment, a GWP of 0.45-0.70 kg CO2,Eq/kWhel was revealed for the electricity production from HTC-char. It, thus, outcompetes the electricity production from lignite (1.05-1.40 kg CO2,Eq/kWhel).

Parameter Optimization in High-Throughput Testing for Structural Materials.

High-throughput screenings are established evaluation methods in the development of functional materials and pharmaceutical active ingredients. The transfer of this approach to the development of structural materials requires extensive adaptations. In addition to the investigation of new test procedures for the determination of material properties and the treatment of metallic materials, the design of experiments is a research focus. Based on given descriptor target values, the statistical design of experiments determines investigations and treatments for the investigation of these materials. In this context, process parameters also have to be determined, as these have a major influence on the later material properties, especially during the treatment of samples. In this article, a method is presented which determines the process parameters iteratively. The validation of the calculated process parameters takes place based on differential scanning calorimetry used as the furnace for the heat treatment of small batches and particle-oriented peening as the characterization method.

How well can we simulate complex hydro-geomorphic process chains? The 2012 multi-lake outburst flood in the Santa Cruz Valley (Cordillera Blanca, Perú).

Changing high-mountain environments are characterized by destabilizing ice, rock or debris slopes connected to evolving glacial lakes. Such configurations may lead to potentially devastating sequences of mass movements (process chains or cascades). Computer simulations are supposed to assist in anticipating the possible consequences of such phenomena in order to reduce the losses. The present study explores the potential of the novel computational tool r.avaflow for simulating complex process chains. r.avaflow employs an enhanced version of the Pudasaini (2012) general two-phase mass flow model, allowing consideration of the interactions between solid and fluid components of the flow. We back-calculate an event that occurred in 2012 when a landslide from a moraine slope triggered a multi-lake outburst flood in the Artizón and Santa Cruz valleys, Cordillera Blanca, Peru, involving four lakes and a substantial amount of entrained debris along the path. The documented and reconstructed flow patterns are reproduced in a largely satisfactory way in the sense of empirical adequacy. However, small variations in the uncertain parameters can fundamentally influence the behaviour of the process chain through threshold effects and positive feedbacks. Forward simulations of possible future cascading events will rely on more comprehensive case and parameter studies, but particularly on the development of appropriate strategies for decision-making based on uncertain simulation results. © 2017 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.

Modeling and Simulation of a Machining Process Chain for the Precision Manufacture of Polar Microstructure.

This paper presents a functional microstructured surface, named Polar Microstructure. Polar microstructure is a three dimensional (3D) structured surface possessing a pattern of distribution of latitude and longitude micro-topographies with geometrical characteristics, which is similar to that in the Earth's north or south pole. The spacing of its small surface features can achieve form accuracy at the micrometer level. Polar microstructure has great potential for applications in precision measurement of angle displacement based on the characteristics of its surface features. This paper presents the development of a machining process chain system that integrates single point diamond turning (SPDT) and diamond broaching together to fabricate polar microstructure. A framework of a machining process chain system is presented which is composed of input module, design module, simulation module, output module, and metrology module. After that, modeling of the machining process chain composed of SPDT and diamond broaching is built up. The model takes into consideration the initial surface topography of the workpiece. Simulations have been conducted to obtain the optimal machining parameters in each machining process. A series of experiments was conducted for the ultra-precision machining of various types of polar microstructures. The machining results show that the machining process chain system is technically feasible and effective in the precision manufacturing of polar microstructure. The experimental results agree well with the simulated results.

Influence of electrostatic particle interactions on the properties of particulate coatings of titanium dioxide.

HYPOTHESIS: Particulate coatings are used in a wide range of technical applications. The application affecting properties of these coatings depend strongly on the structure formation along the production process. Thus, primary and secondary particle size, size distribution, particle morphology as well as the particle-particle and particle-fluid interactions of the used formulation affect the resulting coating properties. EXPERIMENTS: In this investigation titanium dioxide particles were dispersed in ethanol with a stirred media mill and stabilised electrostatically. Subsequently, the suspension was destabilised to reach specific pH* values and processed into coatings by dip coating. The influence of the pH* value of the suspension on the suspension's properties such as viscosity, agglomerate size and zeta potential and on its application properties such as coating thickness, micro-mechanical properties, abrasion resistance, gloss, roughness and adhesion was examined. FINDINGS: The electrostatic particle interactions show a significant influence on the structure formation as well as on the properties of nanoparticulate coatings. The coating properties are affected by the coating structures on micro-, meso- or macroscopic scale. Selective coating properties were related to the coating structure using the theoretical model of Rumpf. Besides other important process and formulation parameters, for the production of homogeneous, functional coatings with the desired properties a precise adjustment of the particle interactions is necessary.