Progettazione di Materiali e Processi Modulo 1 – Lezione 4 Progettazione e selezione di materiali e processi

In the previous lecture… This frame illustrates the decision-making strategy applied to the selection of a material. The Design requirements (upper left) are expressed as constraints that the material must meet and the objectives, defined in a moment, that are chosen as measures of the excellence of choice. The Data (upper right) takes the form of a database of the attributes of the materials and processes that are possible candidates for the design The comparison engine applies the constraints, eliminating materials that cannot meet the requirements, and then ranks the survivors, using the objectives, to create a short list. The final choice is made by exploring documentation of the top-ranked candidates. Materials indexes The general selection process Computer-aided tools for materials screening (limit, graph, tree) A first example of screening via software

Criteria of excellence: material indices Material index = combination of material properties that limit performance Sometimes a single property Sometimes a combination Either is a material index Stiffness Strength Constraints Objective minimise mass Explore these! The material properties listed in handbooks – density, modulus and so on – are those that are measured to characterize the fundamental properties of materials – the physicists’ view of materials, one might say. The performance of an engineering component depends on the values of these, butit usually depends not on one property but on a combination of two or more – it is these that we call material indices. They, too, are material properties; they are the ones that characterize engineering performance – the engineers’ view of materials, so to speak. The ones highlighted in the red box of this frame all depend on density ρ and modulus E. They provide criteria of merit that allow the merit of a new hybrid to be assessed and compared with existing materials. Remember this one too! 3

Optimized selection using charts 2 3 1 Search area This frame show index-based selection on a real property chart. The selection can be done using a hard copy chart, as illustrated here. The EduPack software gives greater flexibility, allowing the selection line to be moved and additional constraints to be applied. It lists, in the Results window, the materials that meet all the constraints and makes records for them immediately accessible. The list can be ranked by the value of any property used as a constraint or by the value of the index. Here it is interesting to point out an interesting fact brought out by the method. Many components of aircraft are stiffness-limited – the wing spar is an example – and the objective here is to minimize mass. Materials texts often assert that, for aerospace, material with high specific modulus E/ρ are the best choice when stiffness is important. But aluminum and steel have the same value of specific stiffness, and steel is much cheaper that aluminum – so why are wing spars not made of steel? The answer is that they are loaded in bending, and then the correct criterion of choice is not E/ρ but E1/2/ρ . By that criterion aluminum is much better than steel, as the chart shows. Results 22 pass Material 1 2230 Material 2 2100 Material 3 1950 etc... Ranked by Index

Plotting indices as functions Index This is a CES plot of the index E1/2/ρ. The materials captured in the red box have the highest values: magnesium alloys, aluminum alloys, CFRP and certain woods – the materials of aerospace, past and present. Results 22 pass Material 1 2230 Material 2 2100 Material 3 1950 etc... Ranked by Index

Tables

Tables

In this lecture… Examples of selection: Simple examples for mechanical properties Example with thermal properties Introducing the link between materials and processes Examples of screening based on process Multiple quantitative constraints Simple example of selection with two objectives Multiple conflicting objectives This frame illustrates the decision-making strategy applied to the selection of a material. The Design requirements (upper left) are expressed as constraints that the material must meet and the objectives, defined in a moment, that are chosen as measures of the excellence of choice. The Data (upper right) takes the form of a database of the attributes of the materials and processes that are possible candidates for the design The comparison engine applies the constraints, eliminating materials that cannot meet the requirements, and then ranks the survivors, using the objectives, to create a short list. The final choice is made by exploring documentation of the top-ranked candidates.

Materials for oars M = E0.5/ Function Oar i.e. light, stiff beam Length L Bending stiffness S* Toughness Minimum mass Diameter Material Constraints Objective Free variables This frame illustrates the decision-making strategy applied to the selection of a material. The Design requirements (upper left) are expressed as constraints that the material must meet and the objectives, defined in a moment, that are chosen as measures of the excellence of choice. The Data (upper right) takes the form of a database of the attributes of the materials and processes that are possible candidates for the design The comparison engine applies the constraints, eliminating materials that cannot meet the requirements, and then ranks the survivors, using the objectives, to create a short list. The final choice is made by exploring documentation of the top-ranked candidates. M = E0.5/

Materials for Heat Sinks in Electronics

Design Example: Removing heat from microchips Problem Microchips and in general electronic devices generate heat. Temperature has to be kept to acceptable levels. Currently, this is one of the limiting factors in further development of electronics Need Remove heat from microchips

Design Example: Heat Sinks for Electronics

Translation: a heat sink for power electronics Power micro-chips get hot. They have to be cooled to prevent damage. Keep chips below 200 C without any electrical coupling. Design requirements Translation Constraints Maximum service temp > 200 C Good electrical insulator Good thermal conductor (or T-conduction > 25 W/m.K) Here is an example of translation. The chip-array in a high-powered computer consumes only a few watts, but it is very small, so the power density is high, and it all ends up as heat. The heat has to be pumped out to stop the array overheating. Heat sinks have to meet demanding specifications, some of which are listed on the left of this frame. The material of the heat sink must be a good thermal conductor but must also be an electrical insulator to avoid electrical coupling between the chip and the sink. And it must tolerate the maximum working temperature, here 200C. These – translated into limits for material properties – constrain the choice of material. Any material that does not meet the constraints is unacceptable.

Materials for Heat Sinks in Electronics Funcion Heat sink Constraints Good electrical insulation: ρ > 1018 µΩ cm Max service temperature > 150 °C Geometry Objective Maximize heat removal: Maximize thermal conductivity, λ

Screening using a LIMIT STAGE 2. Selection Stages Graph Limit Tree Browse Select Search Tools 1. Selection data Edu Level 2: Materials Thermal properties Min. Max Mechanical properties Maximum service temperature C Thermal conductivity W/m.K Specific heat J/kg.K Electrical properties Electrical conductor or insulator? Good conductor Poor conductor Semiconductor Poor insulator Good insulator Maximum service temp C Limit stage Ceramics Metals Foams Polymers Glasses 0.1 1 10 100 Insulator Thermal conductivity (W/m.K) Conductor 200 25 The frame illustrates screening using a Limit stage, applying the constraints listed for the heat sink to eliminate materials that cannot do the job. The constraint on thermal conductivity (“must be good thermal conductor”) can be applied by stipulating a minimum value, as here, or by ticking the box for “good thermal conductor”. Electrical resistivity is treated in a similar way; this overhead shows the box “good insulator” ticked to select it. Results 3 out of 100 pass Aluminum nitride 140 - 200 Alumina 26 - 38.5 Silicon nitride 22 - 30 Ranking T-conductivity

Screening using a GRAPH STAGE Browse Select Search Tools 1. Selection data Edu Level 2: Materials Max service temp. (C) Metals Polymers Ceramics Composites 2000C 2. Selection Stages Graph Limit Tree 1000 0.1 Metals Polymers & elastomers Composites Foams 1030 1 1010 1020 Ceramics 10 100 0.01 Electrical resistivity (.cm) T-conductivity (W/m.s) Here we show screening using Graph stages. The heat sink is again taken as an example. The CES EduPack software allows bar-charts and bubble charts to be created. A range of selection tools can be applied to them. The uppermost is a (schematic) bar chart of maximum service temperature to which a box selection has been applied. Only the materials in the box are retained. The lower graph shows a bubble chart to which a box selection has been applied to isolate materials with high electrical resistivity and high thermal conductivity. Materials that pass both selection stages are displayed in the Results window, where they can be ranked by the value of any one of the three properties used as constraints. Results 3 out of 100 pass Aluminum nitride 140 - 200 Alumina 26 - 38.5 Silicon nitride 22 - 30 Ranking T-conductivity Don’t need numbers!

Design Example: Heat Sinks for Electronics

The link between the materials kingdom and the processes kingdom database Suppliers data-table References Materials data-table DATA FOR Metals & alloys Polymers Ceramics & glasses Hybrids Processes data-table DATA FOR Joining Shaping Surface treatment Links Select on links This overhead shows the structure of the CES EduPack database. It contains 4 linked data-tables: Materials: metal, polymers, ceramics and hybrids Processes for shaping, joining and finishing materials References to more information about any given record in the data-tables Supplier information for materials or processes. Each record in the Materials data-table contains data for material properties, and is linked to similar records for the processes that can shape, join and finish it. Each record in the Process data-table is similarly linked to the materials it can treat and to reference and supplier information. This allows selection of materials by specifying required properties, or by specifying how it can be processed.  

Translation: an example of redesign CD cases are made of polystyrene (PS). They crack and scratch the disks. Find a better material. Retain what is good Replace what is bad The principle Injection-moldable As transparent as PS Can be recycled Contain and protect CD better than the PS case. Design requirements Translation Constraints Can be injection molded Optically clear Can be recycled Like PS Tree stage! Here is a second example of translation. The task is one of redesign – finding a material for a CD case that has the good qualities of the standard polystyrene “jewel” case but is less brittle and will not crack so easily. The design requirements on the left are re-expressed as constraints that the material must fulfil: Ability to be injection molded, allowing large numbers to be made cheaply Optically clear, like polystyrene, so that the label can be read clearly An ability to be recycled at the end of life, making the case environmentally less damaging A fracture toughness that is greater than that of polystyrene to make the case less brittle. All these constraints except the first can be applied with Limit or Graph stages. To impose the constraint that the material can be injection molded we need a Tree stage. . Unlike PS Toughness K1c > that of PS

Screening using a TREE STAGE Browse Select Search Tools 1. Selection data Edu Level 2: Materials Trees Joining Shaping Surface treatment Process Universe + Selected records 2. Selection Stages Graph Limit Tree Results 24 out of 100 pass Material 1 Material 2 Material 3 etc... Materials that can be injection molded Shaping – injection molding – injection mold A Tree stage allows the search to be limited to either: a subset of materials, or materials that can be processed in chosen ways. Opening a Tree stage gives access to the tree-like hierarchical classification of materials (exactly as in the Browse window), or to that of processes. If any part of either tree is selected, only materials that belong to that subset of materials, or that can be processed in the chosen way, are retained. Here the selection is that of materials that can be injection molded.

The CD case: the whole story Tree stage: injection mold Optical properties Transparency Eco properties Recycle Optical quality Transparent Translucent Opaque  Translation Constraints Can be injection molded Optically clear Can be recycled Toughness K1c > that of PS Fracture toughness Polystyrene Keep these! This frame illustrates selection to find a substitute for polystyrene (PS) for the CD case. The method is to identify the properties of PS that are desirable, and insist that the substitute meets or exceeds these, and the property of PS that is undesirable – here, the fracture toughness – and insist the the substitute have a better value of this. This method is a general one for seeking substitutes. Often the undesirable property is price. Then the ideas is to seek materials with relevant properties that match or exceed the currently used material but are cheaper.

Materials for riot shields Protective visor for law enforcers Design requirement Translation Constraints Transparent - of optical quality Tough – high fracture toughness Able to be molded Young’s modulus GPa Yield strength MPa Fracture toughness MPa.m1/2 Mech. properties Min. Max. Optical properties. Opaque Translucent Transparent Optical quality Transparency Limit stage Plus graph stage Best choice: Polycarbonate ? Here is an example of how limit and graph stages can be combined during screening.

Materials for table legs - a simple example of multiple objectives - Function Oar i.e. light, stiff beam Length L No bucking No fracture Minimum mass Maxiumum slenderness Diameter Material Constraints Objective Free variables This frame illustrates the decision-making strategy applied to the selection of a material. The Design requirements (upper left) are expressed as constraints that the material must meet and the objectives, defined in a moment, that are chosen as measures of the excellence of choice. The Data (upper right) takes the form of a database of the attributes of the materials and processes that are possible candidates for the design The comparison engine applies the constraints, eliminating materials that cannot meet the requirements, and then ranks the survivors, using the objectives, to create a short list. The final choice is made by exploring documentation of the top-ranked candidates. M1 = E0.5/ M2 = E