Launching Fluent from Windows Machine to Linux HPC using PBS Pro in PyFluent

### 🔍 Before submitting the issue

- [x] I have searched among the existing issues
- [x] I am using a Python virtual environment

### 🐞 Description of the bug

I am used to launching Fluent GUI from a Windows machine connected to a Linux HPC. I am trying to adapt this workflow to PyFluent. I am struggling to launch to the HPC in my code, and haven't found good documentation on launching using PBSPro job scheduler.

This is the existing code that is not working:
solver = pyfluent.launch_fluent(
precision=pyfluent.Precision.DOUBLE,
processor_count=264,
show_gui=True,
additional_arguments='-rsh="plink -batch -i C:\Temp\ssh-priv.ppk -l bv169" '
'-nodepath=/opt/ohpc/pub/apps/ansys_inc/v241/fluent ' '-node0=XX.XXX.XXX.XX ' #cluster IP
'-setenv="FLUENT_REMOTE_SSH=1" '
'-pbs '
'-pbssubmissionhost=XX.XXX.XXX.XX' #cluster IP
)

### 📝 Steps to reproduce

Launching from the command prompt on Windows machine logged into Python environment with PyFluent installed. Previous lines of code:
import os
import pandas as pd
from ansys.fluent.core import launch_fluent
import ansys.fluent.core as pyfluent

### 💻 Which operating system are you using?

Windows

### 📀 Which ANSYS version are you using?

2024 R1

### 🐍 Which Python version are you using?

3.12

### 📦 Installed packages

```shell
aiohappyeyeballs==2.6.1
aiohttp==3.11.15
aiosignal==1.3.2
ansys-api-fluent==0.3.35
ansys-api-platform-instancemanagement==1.1.2
ansys-api-tools-filetransfer==0.1.1
ansys-fluent-core==0.31.dev0
ansys-platform-instancemanagement==1.1.2
ansys-tools-filetransfer==0.1.1
ansys-units==0.4.0
anyio==4.9.0
argon2-cffi==23.1.0
argon2-cffi-bindings==21.2.0
arrow==1.3.0
asttokens==3.0.0
attrs==25.3.0
beautifulsoup4==4.13.3
bleach==6.2.0
certifi==2025.1.31
cffi==1.17.1
charset-normalizer==3.4.1
click==8.1.8
cmocean==4.0.3
colorama==0.4.6
colorcet==3.1.0
comm==0.2.2
contourpy==1.3.1
cycler==0.12.1
decorator==5.2.1
defusedxml==0.7.1
docker==7.1.0
executing==2.2.0
fastjsonschema==2.21.1
fonttools==4.56.0
fqdn==1.5.1
frozenlist==1.5.0
googleapis-common-protos==1.69.2
grpcio==1.71.0
grpcio-health-checking==1.62.3
grpcio-status==1.62.3
idna==3.10
imageio==2.37.0
importlib_metadata==8.6.1
ipython==9.0.2
ipython_pygments_lexers==1.1.1
ipywidgets==8.1.5
isoduration==20.11.0
jedi==0.19.2
Jinja2==3.1.6
joblib==1.4.2
jsonpointer==3.0.0
jsonschema==4.23.0
jsonschema-specifications==2024.10.1
jupyter-events==0.12.0
jupyter_client==8.6.3
jupyter_core==5.7.2
jupyter_server==2.15.0
jupyter_server_proxy==4.4.0
jupyter_server_terminals==0.5.3
jupyterlab_pygments==0.3.0
jupyterlab_widgets==3.0.13
kiwisolver==1.4.8
lxml==5.3.1
markdown-it-py==3.0.0
MarkupSafe==3.0.2
matplotlib==3.10.1
matplotlib-inline==0.1.7
mdurl==0.1.2
meshio==5.3.5
mistune==3.1.3
more-itertools==10.6.0
msgpack==1.1.0
multidict==6.3.0
nbclient==0.10.2
nbconvert==7.16.6
nbformat==5.10.4
nest-asyncio==1.6.0
nltk==3.9.1
numpy==2.2.4
overrides==7.7.0
packaging==24.2
pandas==2.2.3
pandocfilters==1.5.1
parso==0.8.4
pillow==11.2.0
platformdirs==4.3.7
pooch==1.8.2
prometheus_client==0.21.1
prompt_toolkit==3.0.50
propcache==0.3.1
protobuf==4.25.6
pure_eval==0.2.3
pyansys-tools-report==0.8.2
pycparser==2.22
Pygments==2.19.1
pyparsing==3.2.3
python-dateutil==2.9.0.post0
python-json-logger==3.3.0
pytz==2025.2
pyvista==0.44.2
pywin32==310
pywinpty==2.0.15
PyYAML==6.0.2
pyzmq==26.3.0
referencing==0.36.2
regex==2024.11.6
requests==2.32.3
rfc3339-validator==0.1.4
rfc3986-validator==0.1.1
rich==14.0.0
rpds-py==0.24.0
scikit-learn==1.6.1
scipy==1.15.2
scooby==0.10.0
Send2Trash==1.8.3
setuptools==78.1.0
simpervisor==1.0.0
six==1.17.0
sniffio==1.3.1
soupsieve==2.6
stack-data==0.6.3
terminado==0.18.1
threadpoolctl==3.6.0
tinycss2==1.4.0
tornado==6.4.2
tqdm==4.67.1
traitlets==5.14.3
trame==3.8.1
trame-client==3.6.1
trame-server==3.4.0
trame-vtk==2.8.15
trame-vuetify==2.9.0
types-python-dateutil==2.9.0.20241206
typing_extensions==4.13.0
tzdata==2025.2
uri-template==1.3.0
urllib3==2.3.0
vtk==9.3.1
wcwidth==0.2.13
webcolors==24.11.1
webencodings==0.5.1
websocket-client==1.8.0
widgetsnbextension==4.0.13
wslink==2.3.3
yarl==1.18.3
zipp==3.21.0
```

Start with the reported ansys.fluent.core.launch_fluent call and its PBS Pro additional_arguments from a Windows command prompt using the stated Python environment. Reproduce the failed Windows-to-Linux HPC launch and determine the documented invocation needed for PBS Pro; done means the workflow launches Fluent successfully or the required limitation is clearly documented.

Written by the indexing model from the issue text.