Using multi­physics simu­lations to boost efficiency

Fritz Hoffmeister is developing a multi­physics simu­lation model that will enable a complex electro­chemical machining process to be digitally mapped in full for the very first time.

05.2019 | Text: Thorsten Rienth

Text:
Thorsten Rienth writes as a freelance journalist for AEROREPORT. In addition to the aerospace industry, his technical writing focuses on rail traffic and the transportation industry.

The screen shows two met­al work­pieces: a small, round one on the left, and a larg­er ob­long-shaped one on the right. Small dots dart be­tween them, re­sem­bling a swarm of wasps in a nest. While some take the short­est path, oth­ers go the long way—from the up­per end of the ob­long met­al work­piece right around the back of the small round one, for in­stance. The dots in the swarm rep­re­sent ions in an elec­tric field.

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Act­ing as minute atom-sized shut­tles, the ions dis­solve met­al from the work­piece. In this process of elec­tro­chem­i­cal dis­so­lu­tion, the tool used—which serves as the cath­ode—ex­pe­ri­ences es­sen­tial­ly no wear, of­fer­ing a rev­o­lu­tion­ary ap­proach to ma­chin­ing the high-strength ma­te­ri­als used to pro­duce en­gine air­foils. Sub­trac­tive ma­chin­ing of such met­als would re­sult in tool wear so ex­treme that it would ren­der the whole process too ex­pen­sive.

Elec­tro­chem­i­cal ma­chin­ing, or ECM for short, of­fers up many ques­tions: Which work­ing cur­rent at which feed rate achieves the best geo­met­ric re­sults? How does the cur­rent den­si­ty af­fect the hy­dro­gen gen­er­at­ed in the process and the sur­face qual­i­ty of the work­piece? And, what ef­fect does the pres­sure of the elec­trolyte flow ac­tu­al­ly have on all that any­way? “In the past, we al­ways had to re­ly on tri­al and er­ror to an­swer these ques­tions,” Hoffmeis­ter ex­plains.

A simulation model is set to digitally map all the dif­fer­ent inter­de­pend­encies that occur in the electro­chemical machining of engine airfoils. Hover over the image for a bigger view

A simulation model is set to digitally map all the dif­fer­ent inter­de­pend­encies that occur in the electro­chemical machining of engine airfoils.

aeroreport_effizienz-steigern-mit-multiphysiksimulationen_1

A simulation model is set to digitally map all the dif­fer­ent inter­de­pend­encies that occur in the electro­chemical machining of engine airfoils.

The 29-year-old wrote his master’s thesis on multi­physics simu­lation of the electro­chemical machining process, and it was this paper that first brought him to MTU. Hover over the image for a bigger view

The 29-year-old wrote his master’s thesis on multi­physics simu­lation of the electro­chemical machining process, and it was this paper that first brought him to MTU.

aeroreport_effizienz-steigern-mit-multiphysiksimulationen_2

The 29-year-old wrote his master’s thesis on multi­physics simu­lation of the electro­chemical machining process, and it was this paper that first brought him to MTU.

Out of ne­ces­si­ty—be­cause there was no oth­er way. This ap­proach com­mand­ed a huge amount of time and ef­fort: Set­ting up and run­ning the test, then mea­sur­ing the part. Chang­ing a cou­ple of pa­ra­me­ters. Start­ing again from the top, and then again from scratch for every new part. All the ex­pe­ri­ence MTU has gained with this process nat­u­ral­ly helps to speed things up, but Hoffmeis­ter, who has just turned 29, is look­ing for a much short­er way to achieve the same re­sults. He asked him­self, “What if we were able to sim­u­late all these in­ter­ac­tions with mi­crom­e­ter pre­ci­sion?”

To an­swer that, Hoffmeis­ter opt­ed to take the mul­ti­physics sim­u­la­tion route: “We’re de­vel­op­ing a sim­u­la­tion mod­el that in­cor­po­rates chem­i­cal re­ac­tions, heat trans­fer, mul­ti-phase flu­id flow and the elec­tric field. Es­sen­tial­ly, by sim­u­lat­ing cur­rent flow, we can cal­cu­late the ma­te­r­i­al re­moval rate and con­se­quent­ly the fi­nal geome­tries with ex­treme pre­ci­sion. Put sim­ply, we feed the geome­tries of a new com­po­nent in­to a su­per­com­put­er and run through the it­er­a­tions in a vir­tu­al en­vi­ron­ment. It al­ready works well in 2D, but 3D sim­u­la­tion will be es­sen­tial for in­dus­tri­al ap­pli­ca­tion. We’re work­ing hard on that.”

Hoffmeis­ter earned his bach­e­lor’s de­gree in me­chan­i­cal en­gi­neer­ing be­fore go­ing on to com­plete his MSc in com­pu­ta­tion­al en­gi­neer­ing and sim­u­la­tion at Mu­nich Uni­ver­si­ty of Ap­plied Sci­ences. Dur­ing his stud­ies, Hoffmeis­ter worked at a com­pa­ny in the au­to­mo­tive in­dus­try, where he was re­spon­si­ble for cal­cu­lat­ing ve­hi­cle crash and airbag sim­u­la­tions—the lat­ter us­ing mul­ti­physics. It was his mas­ter’s the­sis—“Nu­mer­i­cal sim­u­la­tion of 3D elec­trolyte flow and the ful­ly cou­pled 2D mul­ti­physics of the ECM process”—that brought Hoffmeis­ter to MTU.

And it’s no co­in­ci­dence that the ti­tle of his pa­per re­flects ex­act­ly what Hoffmeis­ter does at MTU to­day. As his mas­ter’s the­sis was near­ing com­ple­tion, MTU of­fered him a per­ma­nent po­si­tion at the com­pa­ny, which he glad­ly ac­cept­ed.

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