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Astec Industries, a leading manufacturer of hot-mix asphalt plants and soil remediation equipment, faced several challenges in their design and manufacturing process. The company started with CAD models intended solely for manufacturing, which resulted in very complex and imperfect assemblies. They needed to quickly generate parametric studies to determine key design variables, but were constrained by demanding time scales for results. Additionally, there was a vast difference in the scale of detail on most models, further complicating the design and optimization process.

Large tractors require complex cooling systems that consist of five separate modules. Each cooling module is dedicated to one of the engine’s five different fluid systems, includes its own heat exchanger, and is additionally cooled by the main engine fan. The primary goal of the tractor is to support itself and the added extra load of any attachments it has, such as a mower or a plow. This necessitates a design effort that focuses on maximizing engine power output and efficiency of the cooling package, while also optimizing the locations of all the components within the engine compartment to provide enough air to both the engine and the cooling system modules. For CNH, this design process often only included an in-depth analysis of the individual components, for example, each of the cooling modules. There was no simple way to include the effect of component layout within the engine compartment and the distribution of airflow to each module over the entire system. The alternative used by CNH, though expensive and time-consuming, was to develop and test several prototypes to balance cooling with space requirements.

URS Corporation, a leading full-service engineering, planning, design, and construction company, was tasked with performing a comprehensive structural stability evaluation of the McKelvey Lake Dam in Mahoning County, Ohio. The dam, a 77-ft.-high concrete arch structure with a crest length of approximately 350 ft., forms a water reservoir with a maximum storage capacity of 4,345 acre-ft. The challenge was to ensure that repeated freeze-thaw cycles had not compromised the dam's integrity for increased flood loads. Traditionally, such an analysis would involve extensive field investigations to collect concrete and foundation rock samples for laboratory testing. However, this process was time-consuming and costly, especially for dams located in remote areas. Furthermore, the creation of numerous computer models and running a wide range of individual simulations to thoroughly analyze all interrelated variables added to the complexity and cost of the project.

BlueScope Steel Limited, a division in New Zealand, produces 650,000 tons of steel annually from locally sourced iron sand and coal. A crucial part of this process involves the direct reduction of iron sand by char in four rotary kilns. These kilns, large structures with 65 meter-long revolving cylinders, are used to remove oxygen from iron sand to produce a partially reduced material containing the correct amount of carbon for feeding into downstream melters. However, the company faced challenges in understanding the flow patterns, temperature, and concentration contours inside these kilns. Accretion layers or rings, derived mainly from impurities, occasionally form on the inner face of the kiln shell, limiting the production rate. The company needed a solution to this complex problem involving highly turbulent flows, chemical reactions, heat transfer, and a very large geometry in a reasonable time. They also needed to test a range of operating conditions and geometries efficiently.

Navatek Ltd., a leader in researching, developing, and deploying innovative, advanced ship hull designs and associated technologies, faced a significant challenge in their testing process. The traditional method of scale model testing was proving to be time-consuming, expensive, and unreliable due to scaling effects. The complexity of the physics involved in the processes, including transient, transitionally turbulent, multiphase flow with a free surface, added to the difficulty of obtaining reliable and accurate results. This situation necessitated a more efficient, reliable, and cost-effective solution for testing their ship hull designs.

Liebherr-Werk Ehingen GmbH, a leading manufacturer of mobile cranes, faced a significant challenge in their quest to maintain their market and technological leadership. The company needed to develop and market new innovative products and components, as well as increase the workloads of the cranes by leveraging all available technological possibilities. This was crucial to stay ahead in a competitive market and meet the evolving needs of their customers. Additionally, they were also tasked with optimizing their methods and processes to decrease design and analysis time. This was necessary to improve efficiency, reduce costs, and speed up the time-to-market of their products.

Peregrine Consulting, Inc. was tasked by the U.S. Air Force to investigate the feasibility of performing real-time stress and life analysis of jet aircraft engine turbine components based on as-flown conditions. This approach, known as condition-based maintenance (CBM), aimed to provide a reliable prediction of remaining component life for individual aircraft engines by analyzing as-manufactured information and measurable data from each flight. The challenge was to manage a vast amount of information, including the ongoing condition of engine parts, key data on aircraft performance, engine parameters for each flight, and analysis results. The analysis models were extremely large, with millions of degrees-of-freedom requiring lengthy solution times. Furthermore, the simulation involved numerous complex, multi-attribute effects such as frictional contact, stress stiffening, and large deflections of parts.

VIKING GmbH, a subsidiary of ANDREAS STIHL AG & Co. KG, is a manufacturer of gardening equipment including lawn mowers. The company is committed to continually improving the performance of its lawn mowers, specifically in terms of mowing performance and noise emission levels. However, the company faced a challenge in understanding the aerodynamics within the deck of the lawnmower. The curved, double-edged blade of the lawnmower induced a highly unsteady airflow, which resulted in vortices that periodically struck the wall of the chute, impacting both the noise emission levels and the catching performance. The fast blade rotation, unsteady pressure, and high fluctuations of the air velocity within the deck created a complex airflow that made traditional development and measurement methods almost impossible. The company needed to find a way to improve the catching performance and simultaneously meet outdoor noise emissions regulations.

SilMach, a young MEMS (Micro-Electro-Mechanical Systems) design, simulation, and prototyping R&D company based in Besançon, France, faced a significant challenge in the development of their products. The prototyping of MEMS devices is an expensive process, necessitating accurate simulation before manufacturing to ensure the devices perform as designed. The complexity of these devices requires sophisticated coupled physics analysis tools for accurate prediction of their performance. The challenge was to find a solution that could handle the intricate physics involved in creating sensors and actuators within arrays and predict their performance before committing to manufacture.

Audemars Piguet & Cie, a luxury watch manufacturer, faced a significant challenge in the design and manufacturing of their high-precision watch components, specifically the date display mechanism. This mechanism, which changes the date every 24 hours, needs to advance the date in a way that appears instantaneous to the human eye, usually within 0.015 seconds, and must reveal the correct next date. This is achieved through a complex assembly of a jumper, spring, and trigger cam to rotate the display disk exactly one date step. Traditionally, these fine watch mechanisms were designed using prototyping, a costly and iterative process. While simulation could reduce the need for prototypes, the precise and flexible components within the watch mechanism’s dynamic system required extremely accurate nonlinear dynamics capabilities to characterize correctly.

The Engine Research Center (ERC) at the University of Wisconsin–Madison, a leading institution in the study and application of internal combustion (IC) engines, faced significant challenges in grid generation for complex IC engine geometries. These complexities included valved intake and exhaust ports and intricate details like piston/liner crevices. The ERC's work involves the application and development of computer models for simulating flow and combustion in IC engines, with each engine model requiring a computational mesh to solve the turbulence, chemistry, and flow equations that define their problems. As government emissions standards become stricter, the need to incorporate more physics into simulations and more geometric details into the grids has increased. The second major challenge was performing grid resolution studies with these geometrically complex grids once they were built.

Banco Products India Ltd., a leading manufacturer and supplier of equipment such as engine cooling systems and sealing gaskets, faced a significant challenge in the development of their radiators. Radiators, key components in automotive engine cooling systems, must be designed to meet a wide range of conditions due to the diversity of vehicles. The radiator's complex geometry, which includes several thin sheets with thousands of dimples in the radiator core, is required to meet cooling performance and strength requirements. This complexity made simulation difficult. Furthermore, radiator performance is usually determined by the coolant outlet temperature, and Banco designs several types of radiators to meet the cooling requirements of various vehicles. Physically testing each design was not only time-consuming but also costly.

In the competitive world of yachting, particularly in events like the America’s Cup, the smallest changes in geometry can significantly impact the performance of a boat. Team New Zealand (TNZ) was faced with the challenge of optimizing their yacht design without solely relying on physical testing. This was due to the fact that critical flows of air and water, which greatly affect performance, are invisible, making it difficult to understand the reasons behind certain performance levels. Additionally, the traditional yacht design process can be a costly and time-consuming trial-and-error process. Each design iteration often requires the construction of a prototype, which can cost tens of thousands of dollars and take months to build and test. TNZ designers were tasked with analyzing hundreds of potential designs for the most critical components to extract the maximum performance from their previous generation boats.

The Rotorcraft Research Group at Carleton University, which integrates research efforts in rotorcraft aerodynamics, aeroelasticity, aeroacoustics, blade dynamics, and smart structures, faced a significant challenge in their research process. The group's main research program, the SHARCS project, aimed to prove the concept of an actively controlled 'smart' helicopter rotor for the simultaneous reduction of noise and vibration. This required the use of complex CFD simulations that could take weeks of computation time. The solver required a high-quality structured multi-block hexahedral mesh with advanced mesh distribution. However, creating these advanced grids was a difficult and time-consuming task. If each student had to manually create a mesh for each variant being studied, it would significantly limit the research potential and quality. The challenge was to eliminate the manual Hexa meshing burden for the researchers, thereby maximizing their research potential and quality.

Astrobotic Technology, Inc. faced a significant challenge in designing the structural components of the Tranquility Trek spacecraft. The components comprised of aluminum and lightweight composites, where carbon fiber was bonded to aluminum honeycomb to form a high-strength yet lightweight sandwich material. The layered construction and anisotropic properties of the sandwich required specialized pre-processing tools to accurately represent the fiber direction of every layer of carbon. Additionally, specialized post-processing tools were needed to predict sandwich failure. The company also had to consider random loads during launch. Astrobotic needed to test multiple spacecraft configurations under launch conditions to select and refine the best design in a cost-effective manner.

RAETECH Corporation, a company specializing in automotive design and analysis with a focus on the Motorsports arena, was involved in projects from the design and analysis phase through prototype and testing of the finished product. Their experience involves almost every type of automotive component and system. Their structural analysis routine generally includes linear, nonlinear and fatigue analyses, and they also utilize Computational Fluid Dynamics (CFD) where appropriate, especially in engine component designs and A to B comparisons. They firmly believe in closely coupling the design and analysis phases, followed by properly validating the real physical parts. However, they faced challenges in bringing data through the CATIA V4 importer or the Solidworks plug-in, and in creating both solid and surface meshes using Tetra.

Robopac, a leading designer and manufacturer of stretch wrapping machines, was facing a significant challenge with its existing product, Rotowrap. The product was constructed as a metal box with numerous welding seams, which posed potential reliability issues during the rotation of the wrapping arm. The complex design of the Rotowrap was also more costly than competitors’ products. The company was under pressure to develop a new product that was of higher quality, performance, and reliability, but at a lower cost. The challenge was not only to innovate but also to ensure that the new product was more durable and less costly than the existing one to maintain competitiveness in the industry.

Bioana, a company dedicated to the design and development of medical technology, faced significant challenges in the biomedical engineering field. Before a medical device could be implanted in a patient, extensive testing had to be conducted to determine its lifespan, the optimal material for fabrication, and the stresses it must withstand. For instance, prostheses had to be designed to endure the loads generated by body motion and weight, without failing or significant deformation. Similarly, vascular stents needed to supply optimal blood volumes with predetermined flow rates. Evaluating the performance of these and many other medical devices was crucial, and simulation was a key tool in this process. However, the traditional methods of testing were time-consuming and costly.

Kawa Engineering Ltd. was faced with the challenge of locating a powerhouse close to a waterfall for a client in an area with minimal flood risk. The stakes were high as any occurrence of flooding in the powerhouse would result in significant costs. The ideal location would not only mitigate the risk of flooding but also reduce the need for additional components to protect electrical equipment such as generators, turbines, and switch boxes. Furthermore, the right location would determine the cut and fill required for construction, thereby conserving construction resources.

Team Penske, a leading name in American motorsports, faced a significant challenge when they decided to enter the Indy Racing League (IRL) on a full-time basis. The IRL has stringent rules that govern the construction of cars competing in the league. The design team, led by Technical Director Nigel Beresford, had to work within very tight body-design criteria and were limited in what they could change. Major alterations were impossible as competing cars had to use chassis from one of three manufacturers and the same gearbox. Adding to the complexity was the time factor. There was only a five-month window between seasons, and the car had to arrive at the first race tested and ready to win. The design changes were also very restricted during the off-season, and the cars had to be ready by January for testing. The team had no time for back-up plans or mistakes and had to get the design right the first time to give the team optimum performance.

Hennessy Industries, an international aftermarket wheel service manufacturer, was faced with the challenge of designing a frame for a tire-balancing machine that could balance automobile wheels in a shorter time. The new design was required to be approximately the same size, shape, and weight as the old machine. The R&D team needed to attenuate the noise generated by the frame during the start of the balance cycle so that the machine’s sensors could determine whether any imbalance existed. To achieve this, Hennessy Industries partnered with QuEST Global, a company that provides a wide range of engineering solutions.

The U.S.D.A. Forest Products Laboratory, a leading wood research institute, was facing challenges in accurately determining the thermal conductivity of wood, a critical factor in the wood drying process. The conventional equations used for this purpose, developed over 50 years ago, only provided a rough guideline for certain types of wood. This led to lumber mills and wood processing companies having to perform costly and time-consuming trial-and-error tests to determine the proper temperatures and drying times, often resulting in high scrap rates. The heat transfer coefficients of wood depend on many variables including ring density, tree age, initial moisture content, and cell orientation. These characteristics are usually not uniform across all sections of the same tree, with wood structure affected by seasonal weather differences. Furthermore, ring density in small versus large-diameter trees varies widely depending on growth rates for different conditions such as surrounding vegetation and climate.

Motoman, a leading robotics company, faced the challenge of designing a new system, the MotoSweep O, which would mount a 6-axis robot on a boom and riser system. The system was intended to service multiple vertical and/or horizontal machines from overhead in a linear, rotary, or facing configuration. The rotating arm of the system was designed to reach all machines simultaneously, thereby freeing up significant floor space. The existing servo gallows system, used for overhead arc welding, was to be replaced with a system that could also handle material handling. The new system was intended to reduce the boom's mass, increase the overall payload, and allow a robot larger than the existing maximum of 280kg to be mounted on the boom. The team also aimed to solve the problem of backlash in the main drive assembly of the boom, which caused the boom to shake when the robot reached its program point, increasing the robot’s settling time and the MotoSweep O’s cycle time.

The commercial fan market has been shifting from large custom-designed fan systems to more standardized factory-manufactured units. In response to this trend, AcoustiFLO aimed to develop an efficient small centrifugal fan that could be marketed as a standardized, modular component suitable for packaged air handlers. The concept for this small fan consisted of a centrifugal impeller housed in a vaneless diffuser. However, optimizing the static pressure efficiency of the unit required simultaneous optimization of both the impeller and the diffuser due to their interaction. The engineers at AcoustiFLO found that physical testing was not only cost prohibitive but also failed to provide the necessary insight into the airflow for design improvement. The less powerful CFD software they had been using for simpler design tasks lacked the power to analyze the turbulence and rotational dynamics in the impeller.

Robo-Technology GmbH, a company that specializes in the planning, development, design, manufacturing, and programming of automatic robotic systems, faced a significant challenge. They were tasked with developing an ultrasonic testing system for helicopter parts, which could be up to 6 meters in length. The system required two synchronized 6-axis robots to carry out fast testing movements with high dynamic precision and synchronization. This demanded the highest construction standards, posing a significant challenge for the company. The complexity of the task was further compounded by the need to ensure the rigidity and vibration behavior of the system met the customer's demands.

Trek Bicycle Company, a global leader in bicycle design, manufacturing, and distribution, faced a significant challenge in maintaining its competitive edge in the industry. The company's success hinged on its ability to release innovative products that met stringent strength and stiffness requirements, all while adhering to critical product launch deadlines. A specific challenge was to expedite the market release of a cycle with an assembly composed of an aluminum steer tube bonded with epoxy adhesive into a composite fork that is bolted to the wheel axle. The complexity of the assembly and the need for precision in design and manufacturing posed a significant hurdle in meeting the desired speed to market.

Mohyi Labs, a pioneering company in the field of drone technology, faced significant challenges in the development of their Bladeless Drone. The company was working on a novel Ducted Counter-Vortex Radial Impeller Propulsion technology, but the design optimization process was proving to be a major hurdle. Prior to the involvement of ANSYS, the process required a considerable degree of detective work, relying heavily on indirect methods to deduce the characteristics of the invisible forces at work. While this approach was successful in the early stages, it was time-consuming, significantly increased the difficulty level, and escalated development costs. Mohyi Labs recognized the need for advanced physics simulations to achieve the level of precision engineering required for their project. However, these advanced simulations were, until recently, exclusive to large corporations, academic, and military users.

The Engine NVH Analysis Section at Ford Motor Company is tasked with providing CAE NVH design analysis support to various programs. The types of analysis performed include engine component and assembly modal & vibrational response analysis, engine component and assembly radiated noise analysis, crank/block dynamic interaction analysis, air intake system NVH analysis, and exhaust manifold radiated noise analysis. However, with program timing being regularly compressed, the demand for quick turnaround on design analysis is constantly growing. As the finite element models become larger, they tend to drive the analysis time longer. This creates a need for quick FE models that accurately represent the structures, with the smallest number of degrees of freedom being an absolute necessity. The parts that need to be meshed can range from simple stampings to complex castings of cylinder heads, blocks, and manifolds, to even more complex multi-piece composite intake manifolds.

EADS Innovation Works, a leading global aerospace and defense company, was faced with the challenge of reducing the weight of aircraft parts to achieve cost savings and meet green transportation goals. The load introduction rib (LIR), a critical part of an aircraft’s wing flap, was a particular focus. The aerodynamic loads are transferred through the LIR onto the wing, and engineers needed to analyze the wing flap under conditions of a jammed flap mechanism. This load scenario traditionally required a detailed model of the flap mechanism. To evaluate the failure criteria of a composite LIR, engineers at EADS Innovation Works used an ANSYS Composite PrepPost model and a shell model, and compared the accuracy and workflow efficiency with a traditional solid model.

FMC Technologies India Pvt. Ltd. was faced with the challenge of designing subsea oil and gas equipment that could withstand high pressure and high temperature domains. The equipment had to be qualified per ASME BPVC VIII, Division 3, which requires the cumulative damage on the equipment to be below 1. The increasing depth of oil extraction meant that the structural loading requirements for subsea components were increasing, but there were also space and weight constraints on these components. To reduce over-engineering and promote value engineering, engineers needed to visualize damage distribution in each component. However, ANSYS Structural, the technology they were using, did not have a method to plot damage. The challenge was to develop a customized method using ANSYS’ scripting capabilities.