chapter 4 power tools and equipment answers made in china

2023-05-21 21:22:12

tools driven by compressed air, electricity, or pressurized liquid Shop equipment large shop tools such as floor jacks, parts cleaning tanks, and steam cleaners

Connected to the metal lines from the air compressor Allow the technician to take a source of air pressure to the vehicle being repaired Quick-disconnect connectors allow a technician to connect or disconnect hoses or tools without using a wrench

used to set a specific pressure in the system ( psi, or kPa) Filter traps water so that it can be drained daily Lubricator introduces oil into the airstream increases the life of air tools

Must be used with air wrenches Case hardened, thicker, and much stronger than conventional sockets and extensions Impact tools are flat black, instead of chrome Using a chrome tool on an impact wrench can be unsafe

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In the seventeenth and eighteenth centuries, the predominant thinking was that a successful nation should export more than it imports and that the trade surplus should be used to expand the nation’s treasure, primarily gold and silver. This would allow the country to have a bigger and more powerful army and navy and more colonies.

However, a number of countries—including Japan, South Korea, China, and some other countries in the Far East—have pursued a neomercantilism model in which they seek to grow through an aggressive expansion of exports, coupled with a very measured reduction of import barriers. These countries seek to develop powerful export industries by initially protecting their domestic industry from foreign competition and providing subsidies and other support to stimulate growth, often including currency manipulation.

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EXAMPLE 4-13: Employees are operating tools that generate sparks in the presence of an ignitable gas (workplace condition) exposing them to the danger of an explosion (physical harm). The hazard is use of tools that create sparks in a volatile atmosphere that may cause an explosion capable of seriously injuring employees, not the lack of approved equipment.

EXAMPLE 4-23: The powered industrial truck standard at §1910.178 does not address all potential hazards associated with forklift use. For instance, while this standard deals with the hazards associated with a forklift operator leaving his vehicle unattended or dismounting the vehicle and working in its vicinity, it does not contain requirements for the use of operator restraint systems. An employer’s failure to address the hazard of a tipover (forklifts are particularly susceptible to tipovers) by requiring operators of powered industrial trucks equipped with restraint devices or seat belts to use those devices could be cited under the general duty clause. See CPL 02-01-028, Compliance Assistance for the Powered Industrial Truck Operator Training Standards, dated November 30, 2000, for additional guidance.

EXAMPLE 4-27: The employer is aware of the existence of unguarded power presses that have caused near misses, lacerations, and amputations in the past and has done nothing to abate the hazard.

EXAMPLE 4-32: §1910.217(e)(1)(ii) requires that mechanical power presses be inspected and tested at least weekly. If the machinery is seldom used, inspection and testing prior to each use is adequate to meet the intent of the standard.

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Suggested Citation:"4 Research Tools, Methods, Infrastructure, and Facilities." National Academies of Sciences, Engineering, and Medicine. 2019. Frontiers of Materials Research: A Decadal Survey. Washington, DC: The National Academies Press. doi: 10.17226/25244.

In the past decade, significant advances have been made in the characterization (Section 4.1), synthesis and processing (Section 4.2), and computational (Section 4.3) capabilities available to materials researchers. These new tools have enabled previously unachievable materials insights, and this is especially true when used in combination—for example, in situ measurement and control of novel synthetic strategies or advanced data analytics techniques utilized simultaneously with advanced imaging diagnostics (Section 4.4). Development of these tools is a research frontier in its own right meriting further investment. This chapter highlights a number of methodological advances and the impact they have had on the materials community. One consequence of continually improving tools is the need for infrastructure reinvestment to ensure the availability of state-of-the-art tools (Section 4.5). Novel modalities for such investment are discussed. Last, the current and emerging capabilities available at intermediate-scale facilities as well as national user facilities are highlighted (Section 4.5).

Currently, there is significant ongoing discussion about the development of APT standards. Such developments could help in establishing unified protocols for APT sample preparation, data collection processes, data reconstruction and analysis, and reporting of results worldwide. All these developments could lay the foundation for a bright future for APT as a characterization capability that can take not only materials scientists but also researchers from a variety of disciplines, including geology, biology, and solid-state materials, closer to the goal of achieving the 3D composition, structure, and chemical state of a material atom by atom. Sophisticated data analysis tools are required to extend the reach of the technique beyond visualization, and extract the type of meaningful, quantitative information that is required for the purpose of materials design (e.g., for thermodynamic calculations or grain boundary engineering). Intensive research in this area promises to improve the potential to open up to the application of this powerful technique to a wide range of scientific research areas.

Applications of X rays to quantum materials research include ongoing efforts to understand high-temperature superconductivity, the recent detection and spatial mapping of spin currents using X-ray spectromicroscopy, and the direct demonstration and discovery of new electronic phases of topological quantum matter with angle-resolved photoelectron spectroscopy. Despite this important progress in understanding fundamental material physics, the direct impact of X-ray tools on quantum information technologies has been very low to date. This is because the X-ray tools presently lack the spatial resolution to probe quantum matter on the relevant length scales.

The combined spectral, spatial, and temporal sensitivity enabled by emerging high brightness X-ray sources will dramatically change this situation. X-ray beams are currently typically 10-100 mm in size. In most cases, this is much larger than underlying quantum coherence length and any quantum information is averaged out. The new sources will enable powerful spectroscopic nanoprobes with few-nanometer spatial resolution. These nanoprobes will be able to measure the decoherence of wavefunctions, the influence of device morphology on emergent quantum phenomena, and the motion of quantum information at the heart of emerging quantum technologies. These experiments will investigate not only the spatial and temporal fluctuations of idealized, pure materials but also their manifestation in real-world devices.

The past decade has seen tremendous growth in 3D and four-dimensional (4D) characterization capabilities that are specifically geared toward quantifying mesoscale microstructure and response under stimuli. This growth was made possible by significant advances in computer-based control, sensing, and data acquisition, and has resulted in novel experimental toolsets and methodologies that were not possible a decade ago. These advances have enabled a move from qualitative observations to digital data sets that can be mined, filtered, searched, quantified, and stored with increased fidelity and operability.

orientation textures and gradients. One of the greatest difficulties in 3D data processing and analysis is the lack of well-developed software packages and tools for 3D analysis. Materials researchers must develop custom codes and pipelines. While developing custom processing tools can have certain advantages, it is counterbalanced by the current massive duplication of effort across separate groups, which is further compounded by the lack of standards for data descriptions and file formats that would make interoperable tools easier to develop. As an example, the development of the DREAM.3D software package

At the same time, improvements in experimental tools and accompanying modeling of mechanical properties at nanoscale to micron-scale dimensions have enabled mechanical properties to be quantified at a variety of length scales down to ~100 nm, enabling the quantitative study of micro- and mesoscale unit deformation processes with unprecedented spatial precision. Similarly, a variety of techniques have been reported that allow bulk physical properties such as thermal diffusivity to be accurately measured in micrometer-scale depths. This allows more comprehensive assessments to be made of the mechanical and physical properties of surface-modified materials treated by case hardening or ion implantation/plasma

processing. In addition, these technique advances allow improved quantitative evaluations of the physical and mechanical properties of the near-surface regions of ion-irradiated materials as a proxy to neutron irradiation conditions that could be difficult, costly, and time-consuming (multiple-year experiments) to obtain. As an example, in situ measurements and 3D X-ray characterization of individual grains in polycrystalline bulk materials have paved the way to a better understanding of microstructural heterogeneity and localized deformation in irradiated materials. Such information is critical to the prediction of material aging and degradation in nuclear power plants and the design of new radiation-resistant materials for next-generation nuclear reactors. For instance, researchers have studied in situ heterogeneous deformation dynamics in neutron-irradiated bulk materials using high-energy synchrotron X rays to capture the micro- and mesoscale physics and link it with the macroscale mechanical behavior of neutron irradiated materials of relevance to reactor design.

Given the increase in characterization tool capability and capacity over the past decade, there has been a corresponding need to advance synthesis and processing capabilities. These advanced tools not only facilitate accelerated materials discovery but also enable materials control with resolution consistent with advanced measurements. Often these synthetic advances are facilitated by advanced computational methods for predicting new materials.

Full realization of the promise of precision materials synthesis (size, shape, composition, architecture, etc.) across length scales will transform materials science in a revolutionary way. Specific examples emerging of the possibilities and power of precision synthesis include molecular engineering of catalytic materials for selective reactivity, control of electrochemical energy conversion with atomically precise materials, new biodegradable polymers with control of degradation rate via sequence control, precision placement of nitrogen vacancy center defects in diamond to create materials for quantum information, and self-assembly of peptide amphiphiles into fibrous and micellar structures with extraordinary bioactivity. These are the tip of an iceberg beginning to appear.

The nature and benefits of computation capabilities in MR are extensive, but vary dramatically, depending on the material class or application. For example, the useful computational tools for the well-developed semiconductor and aerospace industries are very different from those needed for new materials, where there are still basic questions and no elaborate databases for mining or application of artificial intelligence. However, it is clear that computational capabilities, on both the large as well as the small scale, will continue to advance large expanses of the MR landscape.

Computational methods integrated with material property databases have successfully been used to recently develop two forms of steel that were licensed to a U.S. steel producer (by QuesTek Innovation, LLC), and then deployed into demanding applications. The first alloy was for the U.S. Air Force (USAF): Ferrium S53, an ultra-high-strength and corrosion-resistant steel that eliminates toxic cadmium plating, and is now flying as safety-critical landing gear on USAF A-10, T038, C-5, and KC-135, and on numerous SpaceX rocket flight-critical components. The second alloy was for the U.S. Navy: Ferrium M54, an upgrade from legacy alloys, which offers more than twice the lifetime of the incumbent steel while saving $3 million in overall program costs and is now deployed on their T-45 safety-critical hook shank component. As seen in Box 2.2 in Chapter 2, the time from development to deployment was reduced from 8.5 years for Ferrium S53 (deployment in 2008) to 4 years for Ferrium M54 using only one design iteration (qualification in 2014). QuesTek has designed, also using integrated methods, a third steel: Ferrium C64, which is a best-in-class gear steel that allows for increased power density, fuel efficiency, and lift of military helicopters. This steel has been patented and is now available for purchase.

Over the past decade, there has been an increasing translation of computational tools to industrial application: the boxes in Chapter 2 provide examples in alloy development and industrial processing. Continuum-state variable process models are used in manufacturing for casting, forging, rolling, vapor deposition, machining, and so on. Further, CALPHAD and the DICTRA (diffusion module of computer code for Thermo-Calc) diffusion code and method are ubiquitous and heavily supported by industry. The transition of other tools—for example, phase field, kinetic Monte Carlo, and so on—are in progress. Progress has been made in physics-based multiscale models for mechanical behavior prediction, but these have yet to be adopted by industry.

Other advances have been achieved through co-design of experiment and computational infrastructure, which has come to the fore in the past decade. Examples include progress in image recognition for microstructure identification and the use of the parallel advances in brightness and power from scattering methods, such as X-ray and neutron scattering, and computational materials science that promise to advance the field of scattering science by elevating the interrogation of data from scattering experiments.

Some of the achievements of the past decade in using machine learning, a heavily data-driven technique, to advance materials understanding were summarized in Section 4.3.3. Other uses of materials data, combined with data mining tools, are to search for new materials compositions. Such searches could include new thermoelectric compounds, and for AM, new aluminum alloy compositions. Materials data combined with data mining can also be applied for microstructure development based on processing conditions. More recently, researchers have been combining these tools with robotics and in situ process monitoring and characterization to build autonomous research apparatuses like the Autonomous Research System developed by Air Force Research Laboratory researchers to determine optimum growth conditions for carbon nanotubes.

data with others as well as data analysis tools and services to commercial customers based on the vast wealth of materials data they are accumulating.

While alluded to in discussions throughout the report, the integration of the different types of tools used by materials researchers presents its own set of opportunities and challenges, some of which are discussed in this section.

Accompanied by advances in first-principles calculations, molecular-dynamics simulations, machine learning, and other data analytics tools, predictive material design is fast becoming the norm, accelerating materials discovery. There is, of course, necessary caution to be applied and further advances to be made before predictive modeling attains the kind of robustness necessary for industrial applications. For example, for the new generation of accurate but still approximate calculations, what are their errors? Standard and well-understood protocols have been developed to some extent, particularly in quantum chemistry, but many new techniques have spotty testing. It would be useful to have a clear suite of experimental properties that would serve as a test-bed. These large amounts of experimental data need to be collected in a coherent way. Among the many as-yet unanswered questions are the following: How do researchers encode all the differences in processing material samples? How do researchers extract what’s relevant from what’s not? Can researchers predict whether a substance can be doped (solubility), and

Despite ever-increasing fidelity of and access to experimental facilities, opportunities still exist to fine-tune experimental conditions, accelerate analysis of the data, and move toward high-throughput screening of materials (see the preceding section) by coupling the instruments to computational facilities. Advancements in this area will not only improve the ability to fully interrogate the terabytes of data that can be acquired from a single experiment in a short time period but also change experimental conditions so as to maximize the utility and descriptiveness of the data that are collected. The idea would be to carry out real-time computational analysis of experimental data. For example, while in operando measurements are being taken of a chemical reaction on a nanocatalyst surface, digitized images of the catalyst under reaction conditions, the vibrational frequencies of the reaction intermediates and X-ray photoelectron spectroscopy data of the system could all be made available to a computational “beam line,” which would calculate the same quantities for the “real” geometry and state of the catalyst. Real-time comparison of the two data sets (experimental and computed) would allow both sides to tweak conditions (parameters) until the desired result is obtained. Such a scenario is achievable, given the advances made in the past decade, discussed earlier in this chapter, in tools that can interrogate materials with atomic-scale precision and computational techniques that aim to predict material structure and dynamics under laboratory conditions.

This array of centers, sponsored by various agencies, have been very successful, as judged by the high oversubscription of their use and by the many important results that they have produced and reported. This leads to the conclusion that the expansion of this type of center would be a valuable asset to promote MR in the United States. Such facilities not only empower U.S. researchers but also attract valuable international exchange and collaborations. Furthermore, organized collaboration and planning among existing and new centers as to the nature and types of facilities that they acquire and maintain would also be valuable.

The past decade has seen a revitalization of neutron sciences in the United States. A major stimulus has been the beginnings of operation of the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL), which now operates routinely at powers of over 1 MW and produces the world’s highest peak flux neutron pulses for beam research on materials. The SNS first target station now operates with 19 specialized state-of-the-art instruments dedicated to MR, spanning techniques aimed at structures at the meso-, nano-, or atomic-length scales, and dynamics on the micro- to picosecond time scales. At the same time, the continuous reactor sources of neutrons, including the NIST Center for Neutron Research and the High Flux Isotope Reactor at ORNL, have seen significant improvements in the availability of cold neutron instrumentation. This has greatly increased the ability to perform unique investigations of “large-scale structures,” such as those found in polymers, biomaterials, and solid-state nanoscale systems, as well as measurements of low-energy dynamics with excellent resolution and signal to noise.

The large amount of data produced in modern neutron scattering instruments has in turn produced its own set of challenges, and at present researchers are starting to see early benefits of coupling high-performance computing and neutron scattering data analysis. This trend is also present for X-ray sources and microscopies, tools for integrating large volumes of data with modeling and simulation in real time to guide experiments is leading to closer coupling of experiment and theory.

No element of investment in MR is more important than facilities, instrumentation, and infrastructure. With excellent facilities and instrumentation in place, a considerable amount of important research can be done with no further investment. These tools stimulate and unleash creativity and productivity. Several findings and recommendations aim to improve our national competitive status in this domain.

Finding: The integration of computational control and automation with advanced characterization techniques has made it possible to build 3D data sets that represent materials digitally with greater fidelity than previously imaginable. Methodologies for 3D characterization and analysis are currently developed locally; universally agreed upon process flows, tools, and analysis techniques are badly needed.

Recommendation: The Department of Energy and National Science Foundation should begin in 2020 to support a broad computing program to develop “nextgeneration” and “fitforpurpose” computers. These computers should not only focus on speed but also include improved data analytics and other capabilities. The program should also include support to create and maintain new software and software interfaces (applications programming interfaces and graphical user interfaces) and ensure that the broad materials research community has access to these tools. This support for code development should go not just to centers but also to single principal investigators or small groups.

chapter 4 power tools and equipment answers made in china

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