Design of a Light-Weight Mixed-Material Door                              Through Structural Optimization                 ...
space of the inner is required for up-and-down movement of the glass window, this space was not removedfrom the design reg...
FIGURE 1: FINITE ELEMENT MODEL DETAILSMaterials Considered: The materials considered for optimization were steel, aluminum...
Results And Discussions                        ®The software OptiStruct ver. 10.0 (2010) was used to solve the optimizatio...
topology for the inner had a preponderance of latticed features which implied that it was difficult tomanufacture. Hence, ...
FIGURE 4: FINAL DESIGN OF THE DOOR INNER                                                      ACKNOWLEDGEMENTSThe authors ...
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O os-01 design-of_a_light-weight_mixed_material_door_gm

  1. 1. Design of a Light-Weight Mixed-Material Door Through Structural Optimization Anand Ramani Anshul Kaushik Senior Researcher Researcher Global General Motors R&D Global General Motors R&D rd rd Units 1-3, 3 Floor, Creator Units 1-3, 3 Floor, Creator Bldg., ITPL, Whitefield Road, Bldg., ITPL, Whitefield Road, Bangalore 560 037, INDIA Bangalore 560 037, INDIAAbbreviations: SSTS – Sub-System Technical Specifications, HS – High Strength, LS – Low Strength, Al –Aluminum, Mg – MagnesiumKeywords: Door, Light-weight, Topology Optimization AbstractEmploying commonly considered design materials, a light-weight design of a door structure was arrived at through a sequence ofoptimization studies. Starting from the performance requirements for various load cases specified in the SSTS, the methodologycombined topology and size optimization studies to obtain several design concepts with various material combinations for the doorouter, inner and header frame. Results from these studies established the relationship between the mass of untrimmed door structureand the material composition of its design. Based on these results, one of the lightest concepts was chosen for additional study toarrive at a potential design of the door structure, whose gauge thicknesses were further optimized, resulting in a light-weight designthat satisfies the SSTS performance requirements. The application of optimization methods and multi-material design resulted in about46% mass reduction for the door structure compared to an all-steel design currently in use.Introduction:Light-weighting the body structure and closures with advanced materials and synthesis techniques is beingactively pursued in the automotive industry. Towards this, design concepts are being obtained and refinedusing structural optimization methods. Various prior studies have focused on the light-weight design ofautomotive structures. A comprehensive study in [1] on mass reduction opportunities in automotive bodystructures using light-weight materials identified methods for reduction in the mass of closures andestimated that about 20% to 40% mass savings can be obtained using currently available materialcombinations and some niche materials that are currently not used for automotive design. This studyfocused mainly on the material aspects of weight reduction. Other studies such as [2], [3] and [4] have alsoexplored the possibility of using light-weight materials to reduce the mass of automotive sub-components.Similarly, several optimization studies on the door structure in the literature have considered simultaneoustopology and size optimization – for example, the use of tailor welded blanks in [5] and thicknessoptimization in [6] – resulting in moderate mass savings (5 to 10%). It is expected that larger mass savingscan be obtained by combining multi-material design along with optimization techniques. The optimizationexercise needs to begin with topology optimization so that the design space is fully explored and the bestconcept is chosen for converting to a final design. Also, the entire door needs to be considered as a totalstructural system so that interaction effects between the components are exploited in obtaining the lightestpossible design, while satisfying the performance requirements for all the applicable load cases.Simultaneously, the manufacturability of the design needs to be ascertained. These points are addressedand demonstrated in the present methodology.Process MethodologyThe door structure of a rear door, typical of a large sedan, consists of the door outer, the door inner, itsreinforcements and the header. The door header is predominantly of frame construction with a hollowprismatic section. The door is connected to the body through two door hinges. The design domain foroptimization was obtained from this door structure and consists of the outer, the header and the designspace for the inner as shown in Fig. 1. In addition, there is space for a layer of adhesive material betweenthe inner and the outer.Finite Element Model Details: The finite element model of the door can be grouped into seven componentsas described in Table I. Component meshes are shown in Fig. 1. Although a small slice of the designSimulation Driven Innovation 1
  2. 2. space of the inner is required for up-and-down movement of the glass window, this space was not removedfrom the design region; instead the entire depth of the inner was considered as the design region. Twokinds of element meshes were considered for the inner: (i) a solid mesh as shown in Fig. 1, and (ii) a lattice-shell mesh which is obtained from the solid mesh by first extracting the faces of the solid elements and thendeleting all the duplicate shell elements and all the solid elements. The adhesive layer is modeled as asingle layer of solid elements sandwiched between the meshes of the outer and inner. Rigid links are usedto connect the mesh of the door outer to that of the inner at the hem-line as shown in Fig. 1. In addition,rigid elements are also used to connect the hinges with the door inner and the latch with the door inner.Normally, the header is connected to the door inner structure through header attachment brackets.However, in the optimization model, the structure of the inner is not known a priori. Therefore, the header isconnected to the door inner structure through rigid links as shown in Fig. 1. The full door model with thesolid mesh of the door inner had 45561 elements and 45782 nodes. The full door model with the lattice-shell mesh of the door inner had 104239 elements and 45782 nodes. TABLE I MODEL DETAILS Thickness Number of optimization Number of design # Component Mesh details details solution cases variables 3 mm upper 2725 shell thickness 1 Door outer elements bound 5 (for 5 materials) 1 thickness variable 27426 solid Door inner (solid mesh) elements 27426 topology variables constant thickness of 1 Door inner (lattice-shell 86002 shell mm for the 2 mesh) elements lattice-shells 5 (for 5 materials) 86002 topology variables Upper and lower thickness bounds same 11622 shell as for door 1 (Material is the same 21 thickness variables for 3 Door header elements outer as for door inner) 21 sub-components 2725 solid 1 (material is not allowed 4 Adhesive layer elements to vary) 2725 topology variables 6 mm upper and 0.7 mm 1 (made of HS steel. 835 shell lower thickness Material is not allowed to 4 thicknesses variables for 5 Door hinges elements bound vary) 4 sub-components 6 Rigid elements 1 None Non-design elements (elements in the connecting regions with rigid elements) – not considered for stress 1 (Material is the same 7 satisfaction as for door inner) None 30177 (in the case of solid mesh for door inner) 88753 (in the case of =5x5x1x1x1x1x1 lattice-shell mesh for door Aggregated = 25 solution cases inner)Load Cases and Boundary Conditions: From the sub-system technical specifications (SSTS), load caseswith performance criteria based on structural stiffness, deflections, stresses and natural frequencies wereconsidered for the optimization study. These were: vertical, torsional and header (hinge pillar and lockpillar) rigidity, inner and outer belt-line stiffness, quasi-static stiffness, fundamental frequency and the doorinner panel attachment interface stiffness load cases. Stress limits were imposed for the vertical rigidity,belt-line stiffness and quasi-static stiffness load cases and corresponded to the yield strength of the chosenmaterial. Durability load cases and load cases pertaining to attachment sub-systems were not consideredfor optimization. Further, non-linear and dynamic load cases were not part of the initial optimization studybecause of limitations imposed by the optimization software.Simulation Driven Innovation 2
  3. 3. FIGURE 1: FINITE ELEMENT MODEL DETAILSMaterials Considered: The materials considered for optimization were steel, aluminum ( (Al) and magnesium(Mg). For steel and Al, two material grades – high strength (HS) and low strength ( , (LS) – were considered.These were chosen so as to span the range of real material grades with representative values for thematerial yield strength, in order to study its effect on the optimization results. Properties of all thesematerials are shown in Table II. A Poisson’s ratio of 0.3 was used for metals and a value of 0.36 was used .for the adhesive. TABLE II MATERIAL PROPERTIES Elastic Yield Minimum Density # Material modulus Strength thickness (kg/m3) (x 1011 N/m2) (MPa) (mm) 1 LS steel 2.1 7800 350 0.8 2 HS steel 2.1 7800 1000 0.7 3 LS Al 0.7 2630 100 1.1 4 HS Al 0.7 2630 250 1.1 0.44 1740 125 1.25 5 Mg 0.014 1100 Not used - 6 AdhesiveDesign Variables for Optimization and Optimization Solution Cases: The design variables considered foroptimization were based on the grouping of components as described in Table I. It can be observed that the tnumber of material choices considered for each component and the manner in which the material choiceswere linked between various components resulted in 25 optimization solution cases. Since two modelingoptions were considered for the door inner (solid mesh and lattice shell mesh), this resulted in a total of 50 oor lattice-shellsolution cases.Simulation Driven Innovation 3
  4. 4. Results And Discussions ®The software OptiStruct ver. 10.0 (2010) was used to solve the optimization problem. Solution turn turn-aroundtimes were approximately eight hours for the model with the solid mesh of the inner and 15 hours for themodel with the lattice mesh of the inner. The simulations were performed on a desktop work d work-station with a12 GB RAM, 2.27 GHz CPU and running a 64 64-bit MS-Windows 7 operating system.Mass Variation: Results from all the optimization runs were aggregated into tabular data and are plotted inFig. 2, which shows the mass from the optimization solutions plotted against the material combinations forthe door inner and outer, for both the models of the door inner – the solid mesh and the lattice shell mesh. Itis apparent that the mass trends for both these cases are similar and the model with the lattice mesh for the areinner resulted in lower masses. Because of the potential of the lattice shell model to yield light lattice-shell light-weightdesigns, further discussion of results is focused on the simulations which employed this model of the door employedinner. It can be observed that the total mass of the door ranges between 12.4 kg for the LS steel outer andinner to 5.95 kg for the Mg outer and inner. From practical considerations, since Mg cannot yet be used tomanufacture Class-A surfaces for the outer, the next lightest option is one with a HS Al outer and a Mg sinner, which weighs 6.35 kg. From Fig. 2, i can also be observed that irrespective of the material for the itouter, the mass variation with the material for the inner is nearly constant at about 4.25 kg. The mass constantvariation with outer material is in the range of 2.7 to 3.1 kg, or 2.9 kg on average. For the all-steel design,the mass variation from a LS steel inner and outer to a HS steel inner and outer is about 0.7 kg. Thisdifference reduces to a marginal value of about 0.1 kg for an all erence all-Al design, indicating th the material thatstrength has an insignificant effect on the design mass when lighter materials are considered. FIGURE 2: MASS PLOT FROM THE OPTIMIZATION SOLUTIONSObtaining the Final Design: Since there are a few topology solutions with only small differences in mass,other criteria such as manufacturing and cost were used to select a potential concept for furtherdevelopment. Thus, the concept with LS Al outer an Mg inner and header with a total mass of 6.41 kg was andchosen for obtaining the final design Space was made for up-and-down movement of the window glass design. downand the optimization solution was re re-obtained. The new mass was lower at 6.06 kg (compared to 6.41 kgobtained previously) and is evidence of the presence of multiple-optima for such problems. The resulting optimaSimulation Driven Innovation 4
  5. 5. topology for the inner had a preponderance of latticed features which implied that it was difficult tomanufacture. Hence, additional lattice thicknesses of 1.5 and 2 mm were considered and topologyoptimization solutions were re-obtained, yielding masses of 6.38 and 6.8 kg respectively. The massincreases with increasing lattice thickness, but the preponderance of latticed features decreases, as can beseen in Fig. 3. For the 2 mm lattice thickness, the topology had minimal lattice content and was hencechosen for creating the final design. The design of the door inner was constructed from the topology densitycontours, as shown in Fig. 4. The design mesh of the inner had 8092 shell elements. A layer of solidelements with adhesive material running along the hem-line was used to connect the inner and the outer.Element-wise and zone-wise (by dividing the mesh into a number of zones) thickness optimization for theshell elements of the inner were considered with thickness bounds of (1.25, 5) mm. Both options werecombined with the thickness optimization of the door outer, header and hinges as in Table I. Slightlydifferent masses were obtained in each case. Final optimization iterations were performed after includingthe crash beam (additional thickness variable) and the fixed glass holder, which were not included in theoriginal model. The thickness of the crash beam was not varied, as it was to be determined from crashsimulations. The final mass obtained was 7.12 kg and can be considered to be the final minimum-massdesign of the door structure, confirming that a light-weight design with almost the same mass as thatobtained from topology optimization can be obtained by starting with the topology concept. The design thusobtained was also verified for its performance in nonlinear load cases like nonlinear deflection, dentresistance and oil-canning. The final design of the door inner can be manufactured by a casting process.Benefits SummaryCompared to a structure that was designed without recourse to optimization techniques, and insteadoptimized by conventional trial-and-error modification, about 1.5 kg reduction in mass (17%) was achieved.Compared with an all-steel door structure, the mass reduction from a multi-material design optimization withlight-weight materials is about 6.1 kg (46%).ChallengesAvailability of multi-material and multi-thickness topology optimization, robustness of the optimizationalgorithm, ability to optimize for nonlinear and dynamic load cases, obtaining clear black-and-white solutionsinstead of density contours, etc. can significantly improve design productivity and the quality of the finaldesigns. Methods to address these issues are currently being developed in GM.Future PlansThe results obtained in the present study encourage a more comprehensive effort in creating a practicallight-weight door structure using an Al outer and a cast-Mg inner. Additional manufacturing considerations(such as the spacing and thickness of ribs in the inner, attachment of the header to inner, etc.) need to beaccounted for in this exercise so as to obtain a practical design. Also, performance in other load caseswhich involve interaction with the body-in-white (such as door check durability, side impact requirements,etc.) need to be verified and the design modified accordingly. These will form part of future work.ConclusionsFollowing the process of topology optimization and subsequent gauge optimization, the minimum-massmulti-material design of the untrimmed rear door structure was determined to be about 7.1 kg, which isabout 17% less than one obtained using conventional methods of design, without recourse to optimizationtools. It has been demonstrated that proper use of multi-material synthesis and optimization techniquesstarting from topology optimization can result in light-weight designs. Further improvements in optimizationmethods can enhance design productivity and the quality of the final designs.Simulation Driven Innovation 5
  7. 7. FIGURE 4: FINAL DESIGN OF THE DOOR INNER ACKNOWLEDGEMENTSThe authors would like to thank Anil Sachdev James O’Kane, Naveen Shankar (EASI Engineering), Sachdev,Santosh Swamy, Umesh Nayaka, Shunmugam Bhaskar, Rinaldo Lucchesi, Arnoldo Garcia Kouichi Inaba, Garcia,Prakash Mangalgiri, Narendran Balan and Prabhakar Marur for their inputs, help and reviews lgiri, reviews. REFERENCES[1] Lotus Engineering Inc., “An Assessment of Mass Reduction Opportunities for 2017 2020 Model Year Vehicle Program Submitted An 2017-2020 Program”, to: The International Council on Clean Transportation, 2010.[2] James, M., Kihiu, J. M., Rading, G. O., Kimotho, J. K., “Use of Magnesium Alloys in Optimizing the Weight of Automobile: Curr Current Trends and Opportunities”, Proceedings of the Sustainable Research and Innovation Conference, Vol. 3, 201 2011.[3] Gaines, L., Cuenca, R., Stodolsky, F., Wu, S., “Potential Automotive Uses of Wrought Magnesium Alloys”, Automotive Technology Development Conference, Detroit, 1996.[4] Logan, S., Kizyma, A., Patterson, C., Rama, S., “Lightweight Magnesium Intensive Body Structure”, SAE World Congress, Detroit, Structure”, 2006.[5] Lee, K. H., Shin, J. K., Song, S. I., Yoo, Y. M., Park, G. J., “Automotive Door Design using Structural Optimization and Desi of Design Experiments”, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2003. Journal[6] Hamacher, M., “Optimization of Tailored Blank Concepts for Vehicle Door”, 2nd European HyperW Works Technology Conference, Strasbourg, 2008.Simulation Driven Innovation 7