Frequency Response results from an analysis using On-Demand Expansion?

Andreas Rydin
Andreas Rydin Member, Employee Posts: 2
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edited March 26 in Structures

Consider an analysis that was setup in Ansys Mechanical to use On-Demand Expansion and having multiple load steps defined. I want to create a text file of the frequence response (amplitude of acceleration in X direction) for some nodes. How can it be done with DPF?

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  • Andreas Rydin
    Andreas Rydin Member, Employee Posts: 2
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    edited March 25

    Here is a pyDPF script that will generate output files, for each node, the frequence response for each load step. The script assumes that the *rfrq, *mode and *rst files are located in the same folder (which would be the case if you're solving the modal+harmonic in the same system)

    from ansys.dpf import core as dpf
    import os,re
    import glob
    
    # Result Data
    dpf.start_local_server(ansys_path=r'C:\Program Files\ANSYS Inc\v231')
    res_path = r'D:\Temp\pyDPF\frf\expansion'
    res_file = "file.rfrq"
    resFile_exp = os.path.join(res_path, res_file)
    ds = dpf.DataSources(resFile_exp)
    mode_files = glob.glob(res_path + '/*.mode')
    rst_files = glob.glob(res_path + '/*.rst')
    data_source_up = dpf.DataSources()
    
    for f in mode_files:
        numbers = re.findall(r'\d+', os.path.basename(f))
        data_source_up.set_domain_result_file_path(f, int(numbers[0]))
        print(int(numbers[0]), f)
    if len(rst_files) > 0:
        for f in rst_files:
            numbers = re.findall(r'\d+', os.path.basename(f))
            data_source_up.add_file_path(f, 'rst', True, int(numbers[0]))
            print(int(numbers[0]), f)
    
    ds.add_upstream(data_source_up)
    my_model = dpf.Model(ds)
    
    # Node Scopings
    n_scoping = dpf.Scoping()
    n_scoping.ids = [11091,11061]
    
    #Time Scoping
    ls = my_model.metadata.time_freq_support.time_frequencies
    ls_scoping = ls.scoping.ids
    timeList = dpf.operators.metadata.time_freq_provider(data_sources=ds).outputs.time_freq_support().time_frequencies.data
    time_ids = list(range(1, len(timeList) + 1))
    
    #Acceleration outputs
    acc = dpf.operators.result.acceleration(data_sources=ds,time_scoping=time_ids,mesh_scoping=n_scoping)
    my_model.metadata.release_streams()
    
    for ns in n_scoping.ids:
        nScoping = dpf.Scoping()
        nScoping.ids = [ns]
        acc_rs = dpf.operators.scoping.rescope_fc(fields_container=acc,mesh_scoping=nScoping)
        acc_amp = dpf.operators.math.amplitude_fc(fields_container=acc_rs)
        #Get max/min from the acclacement scoping
        acc_max = dpf.operators.min_max.min_max_fc(fields_container=acc_amp)
        acc_max_output = acc_amp.outputs.fields_container()
    
        acc_Z = acc_max.outputs.field_max().data[:, 0]
        #Loop through the different load steps
        cnt = 0
        for ls in range(1,len(dpf.operators.metadata.time_freq_provider(data_sources=ds).outputs.time_freq_support().time_frequencies.scoping.ids)+1):
            freq_ls = dpf.operators.metadata.time_freq_provider(data_sources=ds).outputs.time_freq_support().time_frequencies.get_entity_data_by_id(ls)
            freq_ls_num = len(freq_ls)
            lcstring = 'Load Case #'+str(ls)
            y_value = acc_Z[cnt:cnt+freq_ls_num]
            freq_value = timeList[cnt:cnt+freq_ls_num]
            #Print to file
            fName = 'Acceleration_'+str(ns)+'_step_'+str(ls)+'.txt'
            with open(fName,'w+') as g:
                j = 0
                while j < len(freq_value):
                    val = str(freq_value[j])+","+str(y_value[j])+"\n"
                    g.write(val)
                    j+=1
            cnt = cnt+freq_ls_num