
**Apache Airflow version**:
1.10.13

**What happened**:
`force_logout_after` should be `force_log_out_after` in the code section https://github.com/apache/airflow/blob/master/airflow/settings.py#L372-L381. As `force_log_out_after` is actually used and written in https://github.com/apache/airflow/blob/c5700a56bb3b9a5b872bda0fe0d3de82b0128bdf/UPDATING.md#unify-user-session-lifetime-configuration.

**What you expected to happen**:
`force_logout_after` is renamed to `force_log_out_after`.
airflow/settings.py
# If the flag is set to False, we remove all handlers from the root logger
# and add all handlers from 'airflow.task' logger to the root Logger. This is done
# to get all the logs from the print & log statements in the DAG files before a task is run
# The handlers are restored after the task completes execution.
DONOT_MODIFY_HANDLERS = conf.getboolean('logging', 'donot_modify_handlers', fallback=False)
CAN_FORK = hasattr(os, "fork")
EXECUTE_TASKS_NEW_PYTHON_INTERPRETER = not CAN_FORK or conf.getboolean(
    'core',
    'execute_tasks_new_python_interpreter',
    fallback=False,
)
ALLOW_FUTURE_EXEC_DATES = conf.getboolean('scheduler', 'allow_trigger_in_future', fallback=False)
# Whether or not to check each dagrun against defined SLAs
CHECK_SLAS = conf.getboolean('core', 'check_slas', fallback=True)
# Number of times, the code should be retried in case of DB Operational Errors
# Retries are done using tenacity. Not all transactions should be retried as it can cause
# undesired state.
# Currently used in the following places:
# `DagFileProcessor.process_file` to retry `dagbag.sync_to_db`
MAX_DB_RETRIES = conf.getint('core', 'max_db_retries', fallback=3)
USE_JOB_SCHEDULE = conf.getboolean('scheduler', 'use_job_schedule', fallback=True)
# By default Airflow plugins are lazily-loaded (only loaded when required). Set it to False,
# if you want to load plugins whenever 'airflow' is invoked via cli or loaded from module.
LAZY_LOAD_PLUGINS = conf.getboolean('core', 'lazy_load_plugins', fallback=True)
# Determines if the executor utilizes Kubernetes
IS_K8S_OR_K8SCELERY_EXECUTOR = conf.get('core', 'EXECUTOR') in {
    executor_constants.KUBERNETES_EXECUTOR,
    executor_constants.CELERY_KUBERNETES_EXECUTOR,
}